Fluoxetine Rescues Excessive Myelin Formation and Psychological Behaviors in a Murine PTSD Model.

Posttraumatic stress disorder (PTSD) is a complex mental disorder notable for traumatic experience memory. Although current first-line treatments are linked with clinically important symptom reduction, a large proportion of patients retained to experience considerable residual symptoms, indicating pathogenic mechanism should be illustrated further. Recent studies reported that newly formed myelin could shape neural circuit function and be implicated in fear memory preservation. However, its role in PTSD remains to be elucidated. In this study, we adopted a restraint stress-induced PTSD mouse model and found that PTSD-related neuropsychiatric symptoms were accompanied by increased myelination in the posterior parietal cortex and hippocampus. Fluoxetine, but not risperidone or sertraline, has a more profound rescue effect on neuropsychological behaviors and myelin abnormalities. Further mechanistic experiments revealed that fluoxetine could directly interfere with oligodendroglial differentiation by upregulating Wnt signaling. Our data demonstrated the correlation between PTSD and abnormal myelination, suggesting that the oligodendroglial lineage could be a target for PTSD treatment.

Real-Time pH Sensor in Bacterial Microenvironments Using Liquid Crystal Core-Shell Microspheres.

It is well-known that the bacterial microenvironment imposes restrictions on the growth and behavior of bacteria. The localized monitoring of microenvironmental factors is appreciated when consulting bacterial adaptation and behavior in the presence of chemical or mechanical stimuli. Herein, we developed a novel liquid crystal (LC) biosensor in a microsphere configuration for real-time 3D monitoring of the bacteria microenvironment, which was implemented by a microfluidic chip. As a proof of concept, a LC gel (LC-Gel) microsphere biosensor was prepared and employed in the localized pH changes of bacteria by observing the configuration change of LC under polarized optical microscopy. Briefly, the microsphere biosensor was constructed in core-shell configuration, wherein the core contained LCE7 (a nematic LC) doped with 4-pentylbiphenyl-4'-carboxylic acid (PBA), and the shell encapsulated the bacteria. The protonation of carboxyl functional groups of the PBA induced a change in charge density on the surface of LCE7 and the orientation of E7 molecules, resulting in the transitions of the LC nucleus from axial to bipolar. The developed LC-Gel microspheres pH sensor exhibited its dominant performance on localized pH real-time sensing with a resolution of 0.1. An intriguing observation from the prepared pH biosensor was that the diverse bacteria impelled distinct acidifying or alkalizing effects. Overall, the facile LC-Gel microsphere biosensor not only provides a versatile tool for label-free, localized pH monitoring but also opens avenues for investigating the effects of chemical and mechanical stimuli on cellular metabolism within bacterial microenvironments.

Shufeng Jiedu capsule alleviates influenza A (H1N1) virus induced acute lung injury by regulating the lung inflammatory microenvironment.

Background: Death caused by respiratory tract infection is one of the leading causes of death in the world today. Shufeng Jiedu Capsule (SFJDC) is a traditional Chinese medicine that has been widely used clinically for coronavirus disease 2019 (COVID-19), H1N1 influenza virus pneumonia and other diseases. Its pharmacological effect is to inhibit inflammation and improve the body's ability to clear viruses. However, the mechanism of SFJDC in the treatment of viral pneumonia, especially its effect on the inflammatory-immune microenvironment of lung tissue remains unclear. Methods: Mice with H1N1 influenza virus pneumonia were used as a model to verify the efficacy of SFJDC through death protection, lung index, viral load, and HE staining of lung tissue. The levels of inflammatory cytokines and chemokines in lung tissue were investigated by multi-analyte immunoassay. The number and proportion of cells in peripheral blood were detected by blood routine. The percentage of infiltrating immune cells in lung tissue was detected by flow cytometry and immunofluorescence. Results: SFJDC (2.2 g/kg·d-1 and 1.1 g/kg·d-1) increased survival rate (P＜0.01, P＜0.05), prolonged the survival period of mice, and alleviated the histopathological damage in lung (P＜0.01). SFJDC (2.2 g/kg·d-1, 1.1 g/kg·d-1 and 0.055 g/kg·d-1) increased body weight(P＜0.01, P＜0.05), improved activity status, reduced the lung index (P＜0.01, P＜0.05) and viral load (P＜0.01). SFJDC (2.2 g/kg·d-1 and 1.1 g/kg·d-1) reduced interleukin-1ß (IL-1ß), interleukin-18(IL-18), tumour necrosis factor α (TNF-α), monocyte chemoattractant protein (MCP), chemokine (C-X-C motif) ligand 1 (CXCL1) (P＜0.01, P＜0.05), and SFJDC (2.2 g/kg·d-1) increased IL-10 levels (P＜0.05) to regulate inflammation. SFJDC (2.2 g/kg·d-1) increased the percentages of CD4+ T cells (P＜0.01), CD8+ T cells (P＜0.05), and B cells(P＜0.05), and decreased F4/80+ macrophages (P＜0.05). Conclusion: Our findings indicated that SFJDC could inhibit inflammation and lung injury while maintaining the function of the adaptive immune response mediated by T and B cells, and promote the clearance of the virus, thereby treating influenza A (H1N1) virus-induced pneumonia.

Sub-pixel target fine spatial feature extraction method based on aperture coding and micro-scanning imaging mechanism.

The small imaging size of targets over long distances results in the loss of geometry and spatial features. Current methods are subject to sampling limitations and cannot accurately capture the spatial features of sub-pixel targets. This paper proposes a method to accurately locate and extract the fine spatial features of sub-pixel targets through aperture coding and micro-scanning imaging. First, the formation mechanism of imaging features for sub-pixel targets is analyzed. Second, the optical aperture is anisotropically coded in different directions to modulate the spreading spots of the target. The primary spreading direction and the center of the anisotropic spreading spots are extracted. The contour and the location of the target are determined from the spreading length and the intersections of the primary spreading directions. Then, the target is sampled by different detector units through various micro-scanning offsets. The pixel units containing different sub-pixel components of the target after offset are determined based on the location results. The fine spatial distribution of the sub-pixel target is reconstructed based on the intensity variations in the pixel units containing the target. Finally, the accuracy of the sub-pixel target fine spatial feature extraction method is validated. The results show a sub-pixel localization error of less than 0.02 and an effective improvement of the sub-pixel target spatial resolution. This paper provides significant potential for improving the ability to capture spatial features of targets over long distances.

Imaging performance prediction of a hypersonic target in a geosynchronous orbit based on multi-dimensional information correlation of radiation, multi-spectral, and polarization.

Hypersonic target detection based on infrared intensity characteristics is easily disturbed by sea surface and cloud flares when detected by space-based optical systems, which results in a low detection rate, high false alarm, and difficulty in stable detection. This paper explores a method to improve target detection performance based on the correlation of infrared radiation, multi-spectral and polarization. Firstly, the comprehensive factors that influence complex ambient illumination, atmospheric transmission, and clutter background on spectral-polarization characteristics of hypersonic targets are analyzed. Based on the global radiation scattering theory, the temperature distribution model of the hypersonic target is established by using FLUENT. The polarization emission and pBRDF model of the target is established, and the radiation polarization transfer model is generated. Secondly, the sea surface temperature distribution is obtained by inversion of Landsat8 remote sensing data. The radiation polarization transfer model of the sea surface is established based on the Cox-Munk model combined with pBRDF and the polarization emission model. Thirdly, the polarization scattering effect of atmospheric particles on the upward radiation of the interaction of the target with the sunlight is considered comprehensively, and the 6SV radiative transfer model is used to calculate the polarization effect of atmospheric particles on the upward radiation transmission of the target and the background. Then, combined with the point diffusion of the optical system and the photoelectric conversion of the detector, the multi-dimensional full-chain imaging prediction model of the hypersonic target-sea background-ambient atmosphere-optical system-detector is established. The imaging characteristics and detection performance of the target in different imaging dimensions are simulated and analyzed with the signal-to-clutter ratio (SCR). The research shows that in the direction of reflected sunlight from the sea surface, the sea surface glare is suppressed and the target is highlighted through a target detection method of multi-dimensional information. This method has better detection results than the infrared multi-spectral detection method.

Identifying key inflammatory genes in psoriasis via weighted gene co-expression network analysis: Potential targets for therapy.

Psoriasis is a globally prevalent chronic inflammatory skin disease. This study aimed to scrutinize the hub genes related to inflammation and potential molecular mechanisms in psoriasis. Utilizing mRNA expression profiles from public datasets GSE13355, GSE78097, and GSE14905, we set up a comprehensive analysis. Initially, we selected differentially expressed genes (DEGs) from psoriasis and control samples in GSE13355, followed by calculating inflammatory indices using genomic set variation analysis (GSVA). Weighted gene co-expression network analysis (WGCNA) was then applied to link significant modules with the inflammatory index. This process helped us identify differentially expressed inflammation-related genes (DE-IRGs). A protein-protein interaction (PPI) network was established, with the molecular complex detection (MCODE) plug-in pinpointing six chemokine genes (CCR7, CCL2, CCL19, CXCL8, CXCL1, and CXCL2) as central hub genes. These genes demonstrated pronounced immunohistochemical staining in psoriatic tissues compared to normal skin. Notably, the CCR7 gene exhibited the highest potential for m6A modification sites. Furthermore, we constructed transcription factor-microRNA-mRNA networks, identifying 139 microRNAs and 52 transcription factors associated with the hub genes. For the LASSO logistic regression model, the area under the curve (AUC) in the training set was 1, and in the two validation cohorts GSE78097 and GSE14905 were 1 and 0.872, respectively. In conclusion, our study highlights six chemokine genes (CCR7, CCL2, CCL19, CXCL8, CXCL1, and CXCL2) as potential biomarkers in psoriasis, providing insights into the immune and inflammatory responses as pivotal instances in disease pathogenesis. These findings pave the way for exploring new therapeutic targets, particularly focusing on chemokine-associated pathways in psoriasis treatment.

Image fusion using Y-net-based extractor and global-local discriminator.

Although some deep learning-based image fusion approaches have realized promising results, how to extract information-rich features from different source images while preserving them in the fused image with less distortions remains challenging issue that needs to be addressed. Here, we propose a well worked-out GAN-based scheme with multi-scale feature extractor and global-local discriminator for infrared and visible image fusion. We use Y-Net as the backbone architecture to design the generator network, and introduce the residual dense block (RDblock) to yield more realistic fused images for infrared and visible images by learning discriminative multi-scale representations that are closer to the essence of different modal images. During feature reconstruction, the cross-modality shortcuts with contextual attention (CMSCA) are employed to selectively aggregate features at different scales and different levels to construct information-rich fused images with better visual effect. To ameliorate the information content of the fused image, we not only constrain the structure and contrast information using structural similarity index, but also evaluate the intensity and gradient similarities at both feature and image levels. Two global-local discriminators that combine global GAN with PatchGAN as a unified architecture help to dig for finer differences between the generated image and reference images, which force the generator to learn both the local radiation information and pervasive global details in two source images. It is worth mentioning that image fusion is achieved during confrontation without fusion rules. Lots of assessment tests demonstrate that the reported fusion scheme achieves superior performance against state-of-the-art works in meaningful information preservation.

MSC microvesicles loaded G-quadruplex-enhanced circular single-stranded DNA-9 inhibits tumor growth by targeting MDSCs.

BACKGROUND: Myeloid-derived suppressor cells (MDSCs) promote tumor growth, metastasis, and lead to immunotherapy resistance. Studies revealed that miRNAs are also expressed in MDSCs and promote the immunosuppressive function of MDSCs. Currently, few studies have been reported on inducible cellular microvesicle delivery of nucleic acid drugs targeting miRNA in MDSCs for the treatment of malignant tumors. RESULTS AND CONCLUSION: In this study, we designed an artificial DNA named G-quadruplex-enhanced circular single-stranded DNA-9 (G4-CSSD9), that specifically adsorbs the miR-9 sequence. Its advanced DNA folding structure, rich in tandem repeat guanine (G-quadruplex), also provides good stability. Mesenchymal stem cells (MSCs) were prepared into nanostructured vesicles by membrane extrusion. The MSC microvesicles-encapsulated G4-CSSD9 (MVs@G4-CSSD9) was delivered into MDSCs, which affected the downstream transcription and translation process, and reduced the immunosuppressive function of MDSCs, so as to achieve the purpose of treating melanoma. In particular, it provides an idea for the malignant tumor treatment.

FT4-to-FT3 ratio is a novel prognostic marker in subacute combined spinal cord degeneration patients.

Objectives: The FT4-to-FT3 ratio (FFR) variations in patients with subacute combined spinal cord degeneration (SCSD) as a potentially useful prognostic indicator are still unknown. This study aimed to investigate the changes of FFR as a potentially valuable prognostic predictor in patients with SCSD. Methods: This study included 144 consecutive SCSD patients who received standard diagnostic and therapeutic procedures between January 2015 and December 2021 and were admitted to the Department of Neurology at the First Affiliated Hospital of Bengbu Medical University. At the time of admission, we gathered data on all patients' demographics, daily routines, previous chronic conditions, medication histories, and other clinical details. For the purpose of measuring FFR, blood samples were specifically taken within 48 h of admission. The degree of neurological impairment of patients was assessed using the functional disability scale at the time of admission. At 6 months following discharge, the Modified Rankin Scale (mRS) was used to evaluate the clinical prognosis. To evaluate the relationship between the FFR and the risks of a poor outcome (mRS > 2), univariate and multivariate logistic regression analysis was utilized. The significance of the FT4/FT3 ratio in predicting the clinical outcomes in SCSD patients 6 months after discharge was assessed using the area under curve-receiver operating characteristic (AUC-ROC). Results: About 90 patients (62.5%) of the 144 patients had poor outcomes, while 54 (37.5%) had favorable outcomes. Higher FFR at admission was independently linked to higher odds of a poor outcome, according to a logistic analysis. With an optimized cutoff value of >2.843, the FFR exhibited the maximum accuracy for predicting a poor outcome, according to the AUC‒ROC curve (AUC 0.731, P < 0.001; sensitivity, 77.8%; specificity, 83.3%). FFR was identified as an independent predictor of poor outcomes by multivariate logistic regression (OR, 2.244; 95% CI, 1.74-2.90; P < 0.001). Conclusions: We discovered that in patients who had a bad result 6 months after discharge, the FFR had dramatically increased at the time of admission, providing a unique prognostic marker in patients with SCSD.

Genetically redirected HBV-specific T cells target HBsAg-positive hepatocytes and primary lesions in HBV-associated HCC.

Background and Aims: HBV-DNA integration in HBV-related hepatocellular carcinoma (HBV-HCC) can be targeted by HBV-specific T cells. SCG101 is an autologous, HBV-specific T-cell product expressing a T-cell receptor (TCR) after lentiviral transduction recognizing the envelope-derived peptide (S20-28) on HLA-A2. We here validated its safety and efficacy preclinically and applied it in an HBV-related HCC patient (NCT05339321). Methods: GMP-grade manufactured cells were assessed for off-target reactivity and functionality against hepatoma cells. Subsequently, a patient with advanced HBV-HCC (Child-Pugh:A, BCLC:B, ECOG:0, HBeAg-, serum HBsAg+, hepatocytes 10% HBsAg+) received 7.9x107 cells/kg after lymphodepletion. Safety, T-cell persistence, and antiviral and antitumor efficacy were evaluated. Results: SCG101, produced at high numbers in a closed-bag system, showed HBV-specific functionality against HBV-hepatoma cells in vitro and in vivo. Clinically, treatment was well tolerated, and all adverse events, including transient hepatic damage, were reversible. On day 3, ALT levels increased to 1404 U/ml, and concurrently, serum HBsAg started decreasing by 3.84log and remained <1 IU/ml for over six months. HBsAg expressing hepatocytes in liver biopsies were undetectable after73 days. The patient achieved a partial response according to mRECIST score with a >70% reduction of target lesion size. Transferred T cells expanded, developed a stem cell-like memory phenotype, and were still detectable after six months in the patient's blood. Conclusions: SCG101 T-cell therapy showed encouraging efficacy and safety in pre-clinical models and in a patient with primary HBV-HCC and concomitant chronic hepatitis B with the capability to eliminate HBsAg+ cells and achieve sustained tumor control after single dosing.

Optimization of the Extraction Process and Biological Activities of Triterpenoids of Schisandra sphenanthera from Different Medicinal Parts and Growth Stages.

Schisandra sphenanthera Rehd. et Wils., as a traditional Chinese medicine, has important medicinal value. In the market, the availability of the fruit of S. sphenanthera mainly relies on wild picking, but many canes and leaves are discarded during wild collection, resulting in a waste of resources. The canes and leaves of S. sphenanthera contain various bioactive ingredients and can be used as spice, tea, and medicine and so present great utilization opportunities. Therefore, it is helpful to explore the effective components and biological activities of the canes and leaves to utilize S. sphenanthera fully. In this study, the response surface method with ultrasound was used to extract the total triterpenoids from the canes and leaves of S. sphenanthera at different stages. The content of total triterpenoids in the leaves at different stages was higher than that in the canes. The total triterpenoids in the canes and leaves had strong antioxidant and antibacterial abilities. At the same time, the antibacterial activity of the total triterpenoids against Bacillus subtilis and Pseudomonas aeruginosa was stronger than that against Staphylococcus aureus and Escherichia coli. This study provides the foundation for the development and utilization of the canes and leaves that would relieve the shortage of fruit resources of S. sphenanthera.

Chemical characterization and comparative analysis of different parts of Cocculus orbiculatus through UHPLC-Q-TOF-MS.

Cocculus orbiculatus (L.) DC. (C. orbiculatus) is a medicinal herb valued for its dried roots with anti-inflammatory, analgesic, diuretic, and other therapeutic properties. Despite its traditional applications, chemical investigations into C. orbiculatus remain limited, focusing predominantly on alkaloids and flavonoids. Furthermore, the therapeutic use of C. orbiculatus predominantly focuses on the roots, leaving the stems, a significant portion of the plant, underutilized. This study employed ultra-high performance liquid chromatography quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF-MS/MS) with in-house and online databases for comprehensive identification of components in various plant parts. Subsequently, untargeted metabolomics was employed to analyze differences in components across different harvest periods and plant sections of C. orbiculatus, aiming to screen for distinct components in different parts of the plant. Finally, metabolomic analysis of the roots and stems, which contribute significantly to the plant's weight, was conducted using chemometrics, including principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), orthogonal partial least squares discriminant analysis (OPLS-DA), and heatmaps. A total of 113 components, including alkaloids, flavonoids, and organic acids, were annotated across the root, stem, leaf, flower, and fruit, along with numerous previously unreported compounds. Metabolomic analyses revealed substantial differences in components between the root and stem compared to the leaf, flower, and fruit during the same harvest period. PLS-DA and OPLS-DA annotated 10 differentiating components (VIP > 1.5, P < 0.05, FC > 2 or FC < 0.67), with 5 unique to the root and stem, exhibiting lower mass spectrometric responses. This study provided the first characterization of 113 chemical constituents in different parts of C. orbiculatus, laying the groundwork for pharmacological research and advocating for the enhanced utilization of its stem.

Evaluation of AlphaFold2 Structures for Hit Identification across Multiple Scenarios.

The introduction of AlphaFold2 (AF2) has sparked significant enthusiasm and generated extensive discussion within the scientific community, particularly among drug discovery researchers. Although previous studies have addressed the performance of AF2 structures in virtual screening (VS), a more comprehensive investigation is still necessary considering the paramount importance of structural accuracy in drug design. In this study, we evaluate the performance of AF2 structures in VS across three common drug discovery scenarios: targets with holo, apo, and AF2 structures; targets with only apo and AF2 structures; and targets exclusively with AF2 structures. We utilized both the traditional physics-based Glide and the deep-learning-based scoring function RTMscore to rank the compounds in the DUD-E, DEKOIS 2.0, and DECOY data sets. The results demonstrate that, overall, the performance of VS on AF2 structures is comparable to that on apo structures but notably inferior to that on holo structures across diverse scenarios. Moreover, when a target has solely AF2 structure, selecting the holo structure of the target from different subtypes within the same protein family produces comparable results with the AF2 structure for VS on the data set of the AF2 structures, and significantly better results than the AF2 structures on its own data set. This indicates that utilizing AF2 structures for docking-based VS may not yield most satisfactory outcomes, even when solely AF2 structures are available. Moreover, we rule out the possibility that the variations in VS performance between the binding pockets of AF2 and holo structures arise from the differences in their biological assembly composition.

Microbial communities of Schisandra sphenanthera Rehd. et Wils. and the correlations between microbial community and the active secondary metabolites.

Background: Schisandra sphenanthera Rehd. et Wils. is a plant used in traditional Chinese medicine (TCM). However, great differences exist in the content of active secondary metabolites in various parts of S. sphenanthera. Do microorganisms critically influence the accumulation of active components in different parts of S. sphenanthera? Methods: In this study, 16S/ITS amplicon sequencing analysis was applied to unravel microbial communities in rhizospheric soil and different parts of wild S. sphenanthera. At the same time, the active secondary metabolites in different parts were detected, and the correlation between the secondary metabolites and microorganisms was analyzed. Results: The major components identified in the essential oils were sesquiterpene and oxygenated sesquiterpenes. The contents of essential oil components in fruit were much higher than that in stem and leaf, and the dominant essential oil components were different in these parts. The dominant components of the three parts were γ-muurolene, δ-cadinol, and trans farnesol (stem); α-cadinol and neoisolongifolene-8-ol (leaf); isosapathulenol, α-santalol, cedrenol, and longiverbenone (fruit). The microbial amplicon sequences were taxonomically grouped into eight (bacteria) and seven (fungi) different phyla. Community diversity and composition analyses showed that different parts of S. sphenanthera had similar and unique microbial communities, and functional prediction analysis showed that the main functions of microorganisms were related to metabolism. Moreover, the accumulation of secondary metabolites in S. sphenanthera was closely related to the microbial community composition, especially bacteria. In endophytic bacteria, Staphylococcus and Hypomicrobium had negative effects on five secondary metabolites, among which γ-muurolene and trans farnesol were the dominant components in the stem. That is, the dominant components in stems were greatly affected by microorganisms. Our results provided a new opportunity to further understand the effects of microorganisms on the active secondary metabolites and provided a basis for further research on the sustainable utilization of S. sphenanthera.

A general model for predicting enzyme functions based on enzymatic reactions.

Accurate prediction of the enzyme comission (EC) numbers for chemical reactions is essential for the understanding and manipulation of enzyme functions, biocatalytic processes and biosynthetic planning. A number of machine leanring (ML)-based models have been developed to classify enzymatic reactions, showing great advantages over costly and long-winded experimental verifications. However, the prediction accuracy for most available models trained on the records of chemical reactions without specifying the enzymatic catalysts is rather limited. In this study, we introduced BEC-Pred, a BERT-based multiclassification model, for predicting EC numbers associated with reactions. Leveraging transfer learning, our approach achieves precise forecasting across a wide variety of Enzyme Commission (EC) numbers solely through analysis of the SMILES sequences of substrates and products. BEC-Pred model outperformed other sequence and graph-based ML methods, attaining a higher accuracy of 91.6%, surpassing them by 5.5%, and exhibiting superior F1 scores with improvements of 6.6% and 6.0%, respectively. The enhanced performance highlights the potential of BEC-Pred to serve as a reliable foundational tool to accelerate the cutting-edge research in synthetic biology and drug metabolism. Moreover, we discussed a few examples on how BEC-Pred could accurately predict the enzymatic classification for the Novozym 435-induced hydrolysis and lipase efficient catalytic synthesis. We anticipate that BEC-Pred will have a positive impact on the progression of enzymatic research.

Quantitative characterization of micro-scanning imaging aliasing and optical parameter optimization.

Imaging aliasing is a common problem in the imaging domain. The aliasing of micro-scanning imaging is difficult to characterize accurately, and the matching relationship between the optical system and micro-scanning sampling is unclear. In this paper, a micro-scanning aliasing analysis model is proposed based on the property of sampling squeeze, in which the transfer functions of the optical system, detector, and digital filter are coupled with the micro-scanning sampling process. First, the imaging aliasing under different micro-scanning sampling modes is evaluated based on the constraint relationship of the transfer functions for each part. The stretch factor of the transfer function under micro-scanning sampling is calculated by utilizing the amount of aliasing. Second, the micro-scanning imaging transfer function under different optical parameters is predicted by the stretch factor, and the results indicate the existence of an optimal F-number that maximizes the micro-scanning performance improvement. Furthermore, the optimal micro-scanning imaging F-numbers for different fill factors are given, and the matching relationship between optical parameters, fill factors and micro-scanning mode is analyzed. Finally, a micro-scanning imaging simulation is performed based on the actual imaging transfer and micro-scanning sampling process. The simulation experiment verifies the accuracy of the micro-scanning aliasing model and gives the consistent test results of the optimal F-number. This paper can provide theoretical support for the matching relationship among micro-scanning imaging parameters, which is of great significance for the refined optimal design of micro-scanning imaging systems.

Unveiling the mechanism of high sugar diet induced advanced glycosylation end products damage skin structure via extracellular matrix-receptor interaction pathway.

BACKGROUND: AGEs accumulate in the skin as a result of a high-sugar diet and play an important role in the skin aging process. OBJECTIVES: The aim of this study was to characterize the mechanism underlying the effect of a high-sugar diet on skin aging damage at a holistic level. METHODS: We established a high-sugar diet mouse model to compare and analyze differences in physiological indexes. The effect of a high-sugar diet on skin aging damage was analyzed by means of a transcriptome study and staining of pathological sections. Furthermore, the differences in the protein expression of AGEs and ECM components between the HSD and control groups were further verified by immunohistochemistry. RESULTS: The skin in the HSD group mice tended toward a red, yellow, dark, and deep color. In addition, the epidermis was irregular with anomalous phenomena, the epidermis was thinned, and the dermis lost its normal structure and showed vacuolated changes. Transcriptomics results revealed significant downregulation of the ECM-receptor interaction pathway, significant upregulation of the expression of AGEs and significant downregulation of the expression levels of COLI, FN1, LM5, and TNC, among others ECM proteins and ECM receptors. CONCLUSIONS: High-sugar diets cause skin aging damage by inducing the accumulation of AGEs, disrupting the expression of ECM proteins and their receptors, and downregulating the ECM-receptor interaction pathway, which affects cellular behavioral functions such as cell proliferation, migration, and adhesion, as well as normal skin tissue structure.

MITF regulates the subcellular location of HIF1α through SUMOylation to promote the invasion and metastasis of daughter cells derived from polyploid giant cancer cells.

High concentrations of cobalt chloride (CoCl2) can induce the formation of polyploid giant cancer cells (PGCCs) in various tumors, which can produce daughter cells with strong proliferative, migratory and invasive abilities via asymmetric division. To study the role of hypoxia­inducible factor (HIF) 1α in the formation of PGCCs, colon cancer cell lines Hct116 and LoVo were used as experimental subjects. Western blotting, nuclear and cytoplasmic protein extraction and immunocytochemical experiments were used to compare the changes in the expression and subcellular localization of HIF1α, microphthalmia­associated transcription factor (MITF), protein inhibitor of activated STAT protein 4 (PIAS4) and von Hippel­Lindau disease tumor suppressor (VHL) after treatment with CoCl2. The SUMOylation of HIFα was verified by co­immunoprecipitation assay. After inhibiting HIF1α SUMOylation, the changes in proliferation, migration and invasion abilities of Hct116 and LoVo were compared by plate colony formation, wound healing and Transwell migration and invasion. In addition, lysine sites that led to SUMOylation of HIF1α were identified through site mutation experiments. The results showed that CoCl2 can induce the formation of PGCCs with the expression level of HIF1α higher in treated cells than in control cells. HIF1α was primarily located in the cytoplasm of control cell. Following CoCl2 treatment, the subcellular localization of HIF1α was primarily in the nuclei of PGCCs with daughter cells (PDCs). After treatment with SUMOylation inhibitors, the nuclear HIF1α expression in PDCs decreased. Furthermore, their proliferation, migration and invasion abilities also decreased. After inhibiting the expression of MITF, the expression of HIF1α decreased. MITF can regulate HIF1α SUMOylation. Expression and subcellular localization of VHL and HIF1α did not change following PIAS4 knockdown. SUMOylation of HIF1α occurs at the amino acid sites K391 and K477 in PDCs. After mutation of the two sites, nuclear expression of HIF1α in PDCs was reduced, along with a significant reduction in the proliferation, migration and invasion abilities. In conclusion, the post­translation modification regulated the subcellular location of HIF1α and the nuclear expression of HIF1α promoted the proliferation, migration and invasion abilities of PDCs. MITF could regulate the transcription and protein levels of HIF1α and participate in the regulation of HIF1α SUMOylation.

Assessing the performance of MM/PBSA and MM/GBSA methods. 10. Prediction reliability of binding affinities and binding poses for RNA-ligand complexes.

Ribonucleic acid (RNA)-ligand interactions play a pivotal role in a wide spectrum of biological processes, ranging from protein biosynthesis to cellular reproduction. This recognition has prompted the broader acceptance of RNA as a viable candidate for drug targets. Delving into the atomic-scale understanding of RNA-ligand interactions holds paramount importance in unraveling intricate molecular mechanisms and further contributing to RNA-based drug discovery. Computational approaches, particularly molecular docking, offer an efficient way of predicting the interactions between RNA and small molecules. However, the accuracy and reliability of these predictions heavily depend on the performance of scoring functions (SFs). In contrast to the majority of SFs used in RNA-ligand docking, the end-point binding free energy calculation methods, such as molecular mechanics/generalized Born surface area (MM/GBSA) and molecular mechanics/Poisson Boltzmann surface area (MM/PBSA), stand as theoretically more rigorous approaches. Yet, the evaluation of their effectiveness in predicting both binding affinities and binding poses within RNA-ligand systems remains unexplored. This study first reported the performance of MM/PBSA and MM/GBSA with diverse solvation models, interior dielectric constants (εin) and force fields in the context of binding affinity prediction for 29 RNA-ligand complexes. MM/GBSA is based on short (5 ns) molecular dynamics (MD) simulations in an explicit solvent with the YIL force field; the GBGBn2 model with higher interior dielectric constant (εin = 12, 16 or 20) yields the best correlation (Rp = -0.513), which outperforms the best correlation (Rp = -0.317, rDock) offered by various docking programs. Then, the efficacy of MM/GBSA in identifying the near-native binding poses from the decoys was assessed based on 56 RNA-ligand complexes. However, it is evident that MM/GBSA has limitations in accurately predicting binding poses for RNA-ligand systems, particularly compared with notably proficient docking programs like rDock and PLANTS. The best top-1 success rate achieved by MM/GBSA rescoring is 39.3%, which falls below the best results given by docking programs (50%, PLNATS). This study represents the first evaluation of MM/PBSA and MM/GBSA for RNA-ligand systems and is expected to provide valuable insights into their successful application to RNA targets.

Recent Progress in Droplet Structure Machining for Advanced Optics.

The development of optical and photonic applications using soft-matter droplets holds great scientific and application importance. The machining of droplet structures is expected to drive breakthroughs in advancing frontier applications. This review highlights recent advancements in micro-nanofabrication techniques for soft-matter droplets, encompassing microfluidics, laser injection, and microfluidic 3D printing. The principles, advantages, and weaknesses of these technologies are thoroughly discussed. The review introduces the utilization of a phase separation strategy in microfluidics to assemble complex emulsion droplets and control droplet geometries by adjusting interfacial tension. Additionally, laser injection can take full advantage of the self-assembly properties of soft matter to control the spontaneous organization of internal substructures within droplets, thus providing the possibility of high-precision customized assembly of droplets. Microfluidic 3D printing demonstrates a 3D printing-based method for machining droplet structures. Its programmable nature holds promise for developing device-level applications utilizing droplet arrays. Finally, the review presents novel applications of soft-matter droplets in optics and photonics. The integration of processing concepts from microfluidics, laser micro-nano-machining, and 3D printing into droplet processing, combined with the self-assembly properties of soft materials, may offer novel opportunities for processing and application development.