Ferric Oxide Nanomaterials and Plant-Rhizobacteria Symbionts Cogenerate Iron Plaque for Removing Highly Chlorinated Contaminants in Dryland Soils.

Rhizosphere iron plaques derived from Fe-based nanomaterials (NMs) are a promising tool for sustainable agriculture. However, the requirement for flooded conditions to generate iron plaque limits the scope of the NM application. In this study, we achieved in situ Fenton oxidation of a highly chlorinated persistent organic pollutant (2,2',4,5,5'-pentachlorobiphenyl, PCB101) through iron plaque mediated by the interaction between α-Fe2O3 NMs and plant-rhizobacteria symbionts under dryland conditions. Mechanistically, the coexistence of α-Fe2O3 NMs and Pseudomonas chlororaphis JD37 stimulated alfalfa roots to secrete acidic and reductive agents as well as H2O2, which together mediated the rhizosphere Fenton reaction and converted α-Fe2O3 NMs into iron plaque rich in Fe(II)-silicate. Further verifications reproduced the Fenton reaction in vitro using α-Fe2O3 NMs and rhizosphere compounds, confirming the critical role of •OH in the oxidative degradation of PCB101. Significant reductions in PCB101 content by 18.6%, 42.9%, and 23.2% were respectively found in stem, leaf, and soil after a 120-d treatment, proving the effectiveness of this NMs-plant-rhizobacteria technique for simultaneously safe crop production and soil remediation. These findings can help expand the potential applications of nanobio interaction and its mediated iron plaque generation for both agricultural practice and soil remediation.

Design, Synthesis, and Biological Evaluation of Chroman Derivatives as PD-1/PD-L1 Antagonists.

Programmed death-ligand 1 (PD-L1) has emerged as a promising therapeutic target for various cancers due to its crucial role in promoting tumor immune evasion. Here, we report a novel class of chroman-like small-molecule PD-L1 inhibitors exhibiting significant activity in inhibiting the PD-1/PD-L1 interaction. Employing a "ring-close" strategy for conformational restriction, we have achieved compound C27, which demonstrates superior PD-1/PD-L1 inhibitory activity compared to the positive control. Molecular dynamics simulation and binding free energy calculation predict that (R)-C27 with inhibitory activity surpassed (S)-C27. The experimental results from bioassay and X-ray structural analysis corroborate these findings. All these results collectively indicate that (R)-C27 is a promising lead compound deserving further exploration.

A pharmacokinetic study comparing the biosimilar HEC14028 and Dulaglutide (Trulicity®) in healthy Chinese subjects.

This study aimed to evaluate the pharmacokinetics (PKs), safety, and immunogenicity of the biosimilar HEC14028 compared to reference Trulicity® (dulaglutide) in healthy male Chinese subjects. This study was a single-center, randomized, open, single-dose, parallel-controlled comparative Phase I clinical trial, including a screening period of up to 14 days, a 17-day observation period after administration, and a 7-day safety follow-up period. A total of 68 healthy male subjects were randomly assigned (1:1) to the test group (HEC14028) and the reference group (dulaglutide) (single 0.75 mg abdominal subcutaneous dose). The primary objective was to evaluate the pharmacokinetic characteristics of HEC14028 and compare the pharmacokinetic similarities between HEC14028 and dulaglutide. The primary PK endpoints were maximum plasma concentration (Cmax) and area under the blood concentration-time curve from zero time to the estimated infinite time (AUC0-∞). The study results showed that HEC14028 and dulaglutide were pharmacokinetically equivalent: 90% confidence interval (CI) of Cmax and AUC0-∞ geometric mean ratios were 102.9%-122.0% and 97.1%-116.9%, respectively, which were both within the range of 80.00%-125.00%. No grade 3 or above treatment emergent adverse events (TEAEs), serious adverse events (SAEs), TEAEs leading to withdrawal from the trial, or TEAEs leading to death were reported in this study. Both HEC14028 and dulaglutide showed good and similar safety profiles, and no incremental immunogenicity was observed in subjects receiving HEC14028 and dulaglutide.

Nomogram to Predict 90-Day All-Cause Mortality in Acute Ischemic Stroke Patients after Endovascular Thrombectomy.

OBJECTIVE: Although Endovascular Thrombectomy (EVT) significantly improves the prognosis of Acute Ischemic Stroke (AIS) patients with large vessel occlusion, the mortality rate remains higher. This study aimed to construct and validate a nomogram for predicting 90-day all-cause mortality in AIS patients with large vessel occlusion and who have undergone EVT. METHODS: AIS patients with large vessel occlusion in the anterior circulation who underwent EVT from May 2017 to December 2022 were included. 430 patients were randomly split into a training group (N=302) and a test group (N=128) for the construction and validation of our nomogram. In the training group, multivariate logistic regression analysis was performed to determine the predictors of 90-day all-cause mortality. The C-index, calibration plots, and decision curve analysis were applied to evaluate the nomogram performance. RESULTS: Multivariate logistic regression analysis revealed neurological deterioration during hospitalization, age, baseline National Institutes of Health Stroke Scale (NIHSS) score, occlusive vessel location, malignant brain edema, and Neutrophil-to-lymphocyte Ratio (NLR) as the independent predictors of 90-day all-cause mortality (all p ≤ 0.039). The C-index of the training and test groups was 0.891 (95%CI 0.848-0.934) and 0.916 (95% CI: 0.865-0.937), respectively, showing the nomogram to be well distinguished. The Hosmer-Lemeshow goodness-of-fit test revealed the p-values for both the internal and external verification datasets to be greater than 0.5. CONCLUSION: Our nomogram has incorporated relevant clinical and imaging features, including neurological deterioration, age, baseline NIHSS score, occlusive vessel location, malignant brain edema, and NLR ratio, to provide an accurate and reliable prediction of 90-day all-cause mortality in AIS patients undergoing EVT.

Contamination and Control of Mycotoxins in Grain and Oil Crops.

Mycotoxins are carcinogenic, teratogenic and mutagenic toxic compounds produced by some filamentous fungi, which are extremely harmful to corn, rice, wheat, peanut, soybean, rapeseed and other grain and oil crops, and seriously threaten environmental safety, food safety and human health. With the rapid increase in the global population and the expansion of the main crop planting area, mycotoxin contamination has increased year by year in agricultural products. The current review aimed to summarize the contamination status and harmful effects of major mycotoxins of grain and oil crops and the environmental factors that impact mycotoxin contamination. Further, control measures of mycotoxin contamination, especially the biological control strategies, were discussed.

Discovery of Novel PD-L1 Small-Molecular Inhibitors with Potent In Vivo Anti-tumor Immune Activity.

Programmed death-ligand 1 (PD-L1) has surfaced as a promising therapeutic target for various cancers due to its pivotal role in facilitating tumor immune evasion. Herein, we report a series of novel small-molecule PD-L1 inhibitors exhibiting remarkable inhibitory activity against the PD-1/PD-L1 interaction (X18: IC50 = 1.3 nM) and reinstating the suppressive effect of PD-L1 on T cells (X18: EC50 = 152.8 nM). Crystallographic studies revealed the binding mode of X18 and PD-L1. Through a rational prodrug design approach, we have successfully optimized the oral pharmacokinetic properties of X22, effectively addressing the poor oral pharmacokinetic profile of PD-L1 small-molecule inhibitors. Notably, X22 demonstrated significant antitumor efficacy in murine models of MC38 and CT26 colon cancer through the upregulation of tumor infiltration and cytotoxicity of CD8+ T cells partially. These findings offer promising prospects for the advancement of PD-L1 inhibitors as innovative agents in cancer immunotherapy.

Predicting pathological complete response to neoadjuvant chemotherapy in breast cancer patients: use of MRI radiomics data from three regions with multiple machine learning algorithms.

OBJECTIVE: To construct a multi-region MRI radiomics model for predicting pathological complete response (pCR) in breast cancer (BCa) patients who received neoadjuvant chemotherapy (NACT) and provide a theoretical basis for the peritumoral microenvironment affecting the efficacy of NACT. METHODS: A total of 133 BCa patients who received NACT, including 49 with confirmed pCR, were retrospectively analyzed. The radiomics features of the intratumoral region, peritumoral region, and background parenchymal enhancement (BPE) were extracted, and the most relevant features were obtained after dimensional reduction. Then, combining different areas, multivariate logistic regression analysis was used to select the optimal feature set, and six different machine learning models were used to predict pCR. The optimal model was selected, and its performance was evaluated using receiver operating characteristic (ROC) analysis. SHAP analysis was used to examine the relationship between the features of the model and pCR. RESULTS: For signatures constructed using three individual regions, BPE provided the best predictions of pCR, and the diagnostic performance of the intratumoral and peritumoral regions improved after adding the BPE signature. The radiomics signature from the combination of all the three regions with the XGBoost machine learning algorithm provided the best predictions of pCR based on AUC (training set: 0.891, validation set: 0.861), sensitivity (training set: 0.882, validation set: 0.800), and specificity (training set: 0.847, validation set: 0.84). SHAP analysis demonstrated that LZ_log.sigma.2.0.mm.3D_glcm_ClusterShade_T12 made the greatest contribution to the predictions of this model. CONCLUSION: The addition of the BPE MRI signature improved the prediction of pCR in BCa patients who received NACT. These results suggest that the features of the peritumoral microenvironment are related to the efficacy of NACT.

CircUSP1 as a novel marker promotes gastric cancer progression via stabilizing HuR to upregulate USP1 and Vimentin.

Circular RNAs (circRNAs) play a crucial role in regulating various tumors. However, their biological functions and mechanisms in gastric cancer (GC) have not been well understood. Here, we discovered a stable cytoplasmic circRNA named circUSP1 (hsa_circ_000613) in GC. CircUSP1 upregulation in GC tissues was correlated with tumor size and differentiation. We observed that circUSP1 promoted GC growth and metastasis. Mechanistically, circUSP1 mainly interacted with the RRM1 domain of an RNA-binding protein (RBP) called HuR, stabilizing its protein level by inhibiting ß-TrCP-mediated ubiquitination degradation. The oncogenic properties of HuR mediated promotive effects of circUSP1 in GC progression. Moreover, we identified USP1 and Vimentin as downstream targets of HuR in post-transcriptional regulation, mediating the effects of circUSP1. The parent gene USP1 also enhanced the viability and mobility of GC cells. Additionally, tissue-derived circUSP1 could serve as an independent prognostic factor for GC, while plasma-derived circUSP1 showed promise as a diagnostic biomarker, outperforming conventional markers including serum alpha-fetoprotein (AFP), carcinoembryonic antigen (CEA) and carbohydrate antigen 199 (CA19-9). Our study highlights that circUSP1 promotes GC progression by binding to and stabilizing oncogenic HuR, thereby facilitating the upregulation of USP1 and Vimentin at the post-transcriptional level. These findings suggest that circUSP1 could be a potential therapeutic target and a diagnostic and prognostic biomarker for GC.

Sodium aescinate ameliorates chronic neuropathic pain in male mice via suppressing JNK/p38-mediated microglia activation.

OBJECTIVE: A study confirmed that sodium aescinate (SA) can effectively relieve bone cancer pain, but its role in neuropathic pain (NP) remains confused. METHODS: Eighty male mice were randomly divided into four groups: sham+vehicle, sham+SA (40 µg/L, intrathecal injection), chronic contraction injury (CCI)+vehicle, CCI+SA. Behavioral assessments were used to evaluate the locomotor activity and paw withdrawal threshold (PWT) of mice. At the end of the study, spinal cord tissues were collected for histopathological analysis. The JNK/p38 signaling activation, Iba-1 expression, pro-inflammatory cytokines levels, and microglia subtype were assessed by western blotting, immunohistochemical staining, enzyme-linked immunosorbent assay, and flow cytometry with CD86/CD206, respectively. RESULTS: Early treatment with SA delayed the development of mechanical allodynia in CCI mice. Repeated SA treatment could prominently increase the reduction of PWT induced by CCI, and improve the locomotor activity of CCI mice. Mechanically, CCI surgery induced significant up-regulation of p-JNK and p-p38 protein levels, increased number and M1/M2 ratio of microglia, as well as pro-inflammatory factors in the spinal cords of mice, which could be blocked after SA administration. CONCLUSIONS: SA might suppress the activation of microglia and neuroinflammation by selectively inhibiting the JNK/p38 signaling pathway, thereby alleviating CCI-induced NP in male mice.

Elucidating the impacts of microplastics on soil greenhouse gas emissions through automatic machine learning frameworks.

With the rise in global plastic production and agricultural demand, the released microplastics (MPs) have increasingly influenced the elemental cycles of soils, leading to notable effects on greenhouse gas emissions. Despite initial research, there remains a gap in establishing a detailed modeling approach that comprehensively explores the impacts of MPs on GHG emissions. Herein, we utilized literature mining to assemble a comprehensive dataset examining the interplays between MPs and emissions of CO2, CH4, and N2O. Five automated machine learning frameworks were employed for predictive modeling. The GAMA framework was particularly effective in predicting CO2 (Q2 = 0.946) and CH4 (Q2 = 0.991) emissions. The Autogluon framework provided the most accurate prediction for N2O emission, though it exhibited signs of overfitting. Interpretability analysis indicated that the type of MPs significantly influenced CO2 emission. Degradable MPs (i.e., polyamide) inherently led to elevated CO2 emission, and the environmental aging further exacerbated this effect. Although both linear and nonlinear correlations between MPs and CH4 emission were not identified, the incorporation of specific MPs that elevate soil pH, augment soil water retention, and cultivate anaerobic conditions may potentially elevate soil CH4 emission. This research underscores the profound influence of MPs on soil GHG emissions, providing vital insights for shaping agricultural policies and soil management practices in the context of escalating plastic use.

Prediction of neoadjuvant chemotherapy pathological complete response for breast cancer based on radiomics nomogram of intratumoral and derived tissue.

BACKGROUND: Non-invasive identification of breast cancer (BCa) patients with pathological complete response (pCR) after neoadjuvant chemotherapy (NACT) is critical to determine appropriate surgical strategies and guide the resection range of tumor. This study aimed to examine the effectiveness of a nomogram created by combining radiomics signatures from both intratumoral and derived tissues with clinical characteristics for predicting pCR after NACT. METHODS: The clinical data of 133 BCa patients were analyzed retrospectively and divided into training and validation sets. The radiomics features for Intratumoral, peritumoral, and background parenchymal enhancement (BPE) in the training set were dimensionalized. Logistic regression analysis was used to select the optimal feature set, and a radiomics signature was constructed using a decision tree. The signature was combined with clinical features to build joint models and generate nomograms. The area under curve (AUC) value of receiver operating characteristic (ROC) curve was then used to assess the performance of the nomogram and independent predictors. RESULTS: Among single region, intratumoral had the best predictive value. The diagnostic performance of the intratumoral improved after adding the BPE features. The AUC values of the radiomics signature were 0.822 and 0.82 in the training and validation sets. Multivariate logistic regression analysis revealed that age, ER, PR, Ki-67, and radiomics signature were independent predictors of pCR in constructing a nomogram. The AUC of the nomogram in the training and validation sets were 0.947 and 0.933. The DeLong test showed that the nomogram had statistically significant differences compared to other independent predictors in both the training and validation sets (P < 0.05). CONCLUSION: BPE has value in predicting the efficacy of neoadjuvant chemotherapy, thereby revealing the potential impact of tumor growth environment on the efficacy of neoadjuvant chemotherapy.

Epithelial thickness remodeling after small incision lenticule intrastromal keratoplasty in correcting hyperopia measured by RTVue OCT.

PURPOSE: To characterize the in vivo corneal epithelial thickness (CET) remodeling profile in a population of eyes after small incision lenticule intrastromal keratoplasty (SMI-LIKE) for hyperopia. METHODS: The CET profile was measured by RTVue-100 Fourier-domain OCT system across the central 6-mm diameter of the cornea of 17 eyes from 12 subjects (five males and seven females) who accepted corneal stromal lens implantation surgery for correcting hyperopia. The CET were measured at positions with a radius of 0-1.0 mm, 1.0-2.5 mm (divided into eight quadrants) and 2.5-3.0 mm (divided into eight quadrants) from the corneal center. Corneal maximum simulated keratometry (Km) was measured by Pentacam HR anterior segment analyzer to analyze CET changes. The examination data of subjects were collected in four time periods, which were preoperative, short-term postoperative (one week after surgery), mid-term postoperative (the last review within 3-6 months after surgery), and long-term postoperative (the last review over 1-2.5 years after surgery). The changes of CET were compared and analyzed in the four time periods. RESULTS: Mean CET in 0-1.0 mm, 1.0-2.5 mm and 2.5-3.0 mm of the cornea decreased in one week after surgery, respectively, as compared to CET in the preoperative period, which turned from 55.06 ± 0.82 µm、54.42 ± 0.75 µm、53.46 ± 0.60 µm to 51.18 ± 1.05 µm (P = 0.005), 49.38 ± 0.70 µm (P = 0.000), 51.29 ± 0.59 µm (P = 0.025). In the mid-term postoperative period, mean CET in 0-1.0 mm and 1.0-2.5 mm areas kept thinner than mean CET in the preoperative period, CET in 0-1.0 mm is 50.59 ± 0.76 µm (P = 0.000),CET in 1.0-2.5 mm is 50.23 ± 0.57 µm (P = 0.000), while mean CET in 2.5-3.0 mm area recovered to the same thickness as the preoperative level, which is 54.36 ± 0.66 µm (P = 1.000), until the long-term period, CET stabilized in the above doughnut pattern. CONCLUSIONS: After stromal lenticule implantation for hyperopia, CET showed a remodeled form of thinning in the 0-2.5 mm area and thickening in the 2.5-3.0 mm area, and remained stable within one year after surgery.

Prediction of postoperative liver metastasis in pancreatic ductal adenocarcinoma based on multiparametric magnetic resonance radiomics combined with serological markers: a cohort study of machine learning.

OBJECTIVE: To construct and validate a multi-dimensional model based on multiple machine leaning algorithms to predict PCLM using multi-parameter magnetic resonance (MRI) sequences with clinical and imaging parameters. METHODS: A total of 148 PDAC retrospectively examined patients were classified as metastatic or non-metastatic based on results at 3 months after surgery. The radiomics features of the primary tumor were extracted from T2WI images, followed by dimension reduction. Then, multiple machine learning methods were used to construct models. Independent predictors were also screened using multifactor logistic regression and a nomogram was constructed in combination with the radiomics model. Area under the receiver operating characteristic curve (AUC) and decision curve analysis (DCA) were used to assess the accuracy and reliability of the nomogram. RESULTS: The diagnostic efficacy of the radiomics model in the training and test set was 0.822 and 0.803, sensitivity was 0.742 and 0.692, and specificity was 0.792 and 0.875, respectively. The diagnostic efficacy of the nomogram in the training and test set was 0.866 and 0.832. CONCLUSION: A radiomics nomogram based on machine learning improved the accuracy of predicting PCLM and may be useful for early preoperative diagnosis.

Relevant mycotoxins in oil crops, vegetable oils, de-oiled cake and meals: Occurrence, control, and recent advances in elimination.

Mycotoxins in agricultural commodities have always been a concern due to their negative impacts on human and livestock health. Issues associated with quality control, hot and humid climate, improper storage, and inappropriate production can support the development of fungus, causing oil crops to suffer from mycotoxin contamination, which in turn migrates to the resulting oil, de-oiled cake and meals during the oil processing. Related research which supports the development of multi-mycotoxin prevention programs has resulted in satisfactory mitigation effects, mainly in the pre-harvest stage. Nevertheless, preventive actions are unlikely to avoid the occurrence of mycotoxins completely, so removal strategies may still be necessary to protect consumers. Elimination of mycotoxin has been achieved broadly through the physical, biological, or chemical course. In view of the steadily increasing volume of scientific literature regarding mycotoxins, there is a need for ongoing integrated knowledge systems. This work revisited the knowledge of mycotoxins affecting oilseeds, food oils, cake, and meals, focusing more on their varieties, toxicity, and preventive strategies, including the methods adopted in the decontamination, which supplement the available information.

Circular RNA CDR1as Mediated by Human Antigen R (HuR) Promotes Gastric Cancer Growth via miR-299-3p/TGIF1 Axis.

Background: Gastric cancer (GC) remains a common malignancy worldwide with a limited understanding of the disease mechanisms. A novel circular RNA CDR1as has been recently reported to be a crucial regulator of human cancer. However, its biological role and mechanism in the GC growth are still far from clear. Methods: Small interfering RNAs (siRNAs), lentivirus or plasmid vectors were applied for gene manipulation. The CDR1as effects on the GC growth were evaluated in CCK8 and colony formation assays, a flow cytometry analysis and mouse xenograft tumor models. A bioinformatics analysis combined with RNA immunoprecipitation (RIP), RNA pull-down assays, dual-luciferase reporter gene assays, Western blot, reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and functional rescue experiments were used to identify the CDR1as target miRNA, the downstream target gene and its interaction with human antigen R (HuR). Results: The CDR1as overexpression promoted the GC growth in vitro and in vivo and reduced the apoptotic rate of GC cells. Its knockdown inhibited the GC cell proliferation and viability and increased the cell apoptotic rate. Proliferation-related proteins PCNA and Cyclin D1 and apoptosis-related proteins Bax, Bcl-2, Caspase-3 and Caspase-9 were regulated. Mechanically, the cytoplasmic CDR1as acted as a miR-299-3p sponge to relieve its suppressive effects on the GC cell growth. Oncogenic TGIF1 was a miR-299-3p downstream target gene that mediated the promotive effects of CDR1as and regulated the PCNA and Bax levels. HuR interacted with CDR1as via the RRM2 domain and positively regulated the CDR1as level and its oncogenic role as well as downstream target TGIF1. Conclusions: CDR1as promotes the GC growth through the HuR/CDR1as/miR-299-3p/TGIF1 axis and could be used as a new therapeutic target for GC.

Down-regulation of PM20D1 is associated with clinical outcomes and prognosis of pregnant patients with diabetes mellitus.

Introduction: The present study aimed to investigate the role of peptidase M20 domain containing 1 (PM20D1) in gestational diabetes mellitus (GDM). Material and methods: This observational study included 189 cases of GDM patients who came to our department between March 2018 and December 2019. Additionally, 100 healthy pregnant individuals who came to physical examination were included as healthy controls during the same period. Western blotting was used to determine the expression of PM20D1 at gestational age 24-28 weeks and gestational age 37-40 weeks. Serum inflammatory factors of C-reactive protein (CRP), interleukin (IL)-1ß, IL-6, and tumor necrosis factor (TNF)-α, as well as leptin and adiponectin, were all measured by ELISA. The GDM related indices were also measured. Results: The expression of PM20D1 was markedly decreased in GDM patients compared with the healthy controls. Patients in the third trimester of pregnancy (gestational age 37-40 weeks) showed significantly lower expression of PM20D1 than patients in the second trimester of pregnancy (gestational age 24-28 weeks). Serum levels of CRP, IL-1ß, IL-6, TNF-α and leptin were remarkably higher and levels of adiponectin were markedly lower in GDM patients at both the second and third trimester of pregnancy. Also, levels of CRP, IL-1ß, IL-6, TNF-α and leptin in GDM patients were the highest at the third trimester of pregnancy. Pearson's analysis showed that PM20D1 was negatively correlated with IL-1ß, IL-6 and leptin and was positively correlated with adiponectin. At the second trimester of pregnancy, patients with lower expression of PM20D1 showed remarkably higher levels of HOMA-IR, fasting insulin, FBG, OGTT-1hPG, OGTT-2hPG, TG and LDL-C, and showed markedly lower levels of HDL-C. Down-regulated PM20D1 predicted poor pregnancy outcomes. Conclusions: Reduced PM20D1 was associated with patients' clinical outcomes and pregnancy outcomes in GDM.

Anti-inflammation is an important way that Qingre-Huazhuo-Jiangsuan recipe treats acute gouty arthritis.

Background: Acute gouty arthritis (AGA) significantly impairs patients' quality of life. Currently, existing therapeutic agents exhibit definite efficacy but also lead to serious adverse reactions. Therefore, it is essential to develop highly efficient therapeutic agents with minimal adverse reactions, especially within traditional Chinese medicine (TCM). Additionally, food polyphenols have shown potential in treating various inflammatory diseases. The Qingre-Huazhuo-Jiangsuan-Recipe (QHJR), a modification of Si-Miao-San (SMS), has emerged as a TCM remedy for AGA with no reported side effects. Recent research has also highlighted a strong genetic link to gout. Methods: The TCM System Pharmacology (TCMSP) database was used to collect the main chemical components of QHJR and AGA-related targets for predicting the metabolites in QHJR. HPLC-Q-Orbitrap-MS was employed to identify the ingredients of QHJR. The collected metabolites were then used to construct a Drugs-Targets Network in Cytoscape software, ranked based on their "Degree" of significance. Differentially expressed genes (DEGs) were screened in the Gene Expression Omnibus (GEO) database using GEO2R online analysis. Subsequently, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed. The DEGs were utilized to construct a Protein-Protein Interaction (PPI) Network via the STRING database. In vivo experimental validation was conducted using colchicine, QHJR, rapamycin (RAPA), and 3-methyladenine (3-MA) as controls to observe QHJR's efficacy in AGA. Synovial tissues from rats were collected, and qRT-PCR and Western blot assays were employed to investigate Ampk-related factors (Ampk, mTOR, ULK1), autophagy-related factors (Atg5, Atg7, LC3, p62), and inflammatory-related factors (NLRP3). ELISA assays were performed to measure inflammatory-related factor levels (IL-6, IL-1ß, TNF-α), and H&E staining was used to examine tissue histology. Results: Network analysis screened out a total of 94 metabolites in QHJR for AGA. HPLC-Q-Orbitrap-MS analysis identified 27 of these metabolites. Notably, five metabolites (Neochlorogenic acid, Caffeic acid, Berberine, Isoliquiritigenin, Formononetin) were not associated with any individual herbal component of QHJR in TCMSP database, while six metabolites (quercetin, luteolin, formononetin, naringenin, taxifolin, diosgenin) overlapped with the predicted results from the previous network analysis. Further network analysis highlighted key components, such as Caffeic acid, cis-resveratrol, Apigenin, and Isoliquiritigenin. Other studies have found that their treatment of AGA is achieved through reducing inflammation, consistent with this study, laying the foundation for the mechanism study of QHJR against AGA. PPI analysis identified TNF, IL-6, and IL-1ß as hub genes. GO and KEGG analyses indicated that anti-inflammation was a key mechanism in AGA treatment. All methods demonstrated that inflammatory expression increased in the Model group but was reversed by QHJR. Additionally, autophagy-related expression increased following QHJR treatment. The study suggested that AMPKα and p-AMPKα1 proteins were insensitive to 3 MA and RAPA, implying that AMPK may not activate autophagy directly but through ULK1 and mTOR. Conclusion: In conclusion, this study confirms the effectiveness of QHJR, a modified formulation of SMS (a classic traditional Chinese medicine prescription for treating gout), against AGA. QHJR, as a TCM formula, offers advantages such as minimal safety concerns and potential long-term use. The study suggests that the mechanism by which QHJR treats AGA may involve the activation of the AMPK/mTOR/ULK1 pathway, thereby regulating autophagy levels, reducing inflammation, and alleviating AGA. These findings provide new therapeutic approaches and ideas for the clinical treatment of AGA.

Coexpression analysis of lncRNAs and mRNAs identifies potential regulatory long noncoding RNAs involved in the inflammatory effects of lipopolysaccharide on bovine mammary epithelial cells.

BACKGROUND: The infection of bovine mammary glands by pathogenic microorganisms not only causes animal distress but also greatly limits the development of the dairy industry and animal husbandry. A deeper understanding of the host's initial response to infection may increase the accuracy of selecting drug-resistant animals or facilitate the development of new preventive or therapeutic intervention strategies. In addition to their functions of milk synthesis and secretion, bovine mammary epithelial cells (BMECs) play an irreplaceable role in the innate immune response. To better understand this process, the current study identified differentially expressed long noncoding lncRNAs (DE lncRNAs) and mRNAs (DE mRNAs) in BMECs exposed to Escherichia coli lipopolysaccharide (LPS) and further explored the functions and interactions of these lncRNAs and mRNAs. RESULTS: In this study, transcriptome analysis was performed by RNA sequencing (RNA-seq), and the functions of the DE mRNAs and DE lncRNAs were predicted by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Next, we constructed a modulation network to gain a deeper understanding of the interactions and roles of these lncRNAs and mRNAs in the context of LPS-induced inflammation. A total of 231 DE lncRNAs and 892 DE mRNAs were identified. Functional enrichment analysis revealed that pathways related to inflammation and the immune response were markedly enriched in the DE genes. In addition, research results have shown that cell death mechanisms, such as necroptosis and pyroptosis, may play key roles in LPS-induced inflammation. CONCLUSIONS: In summary, the current study identified DE lncRNAs and mRNAs and predicted the signaling pathways and biological processes involved in the inflammatory response of BMECs that might become candidate therapeutic and prognostic targets for mastitis. This study also revealed several possible pathogenic mechanisms of mastitis.

Uncovering the anti-obesity constituents in Ginkgo biloba extract and deciphering their synergistic effects.

Obesity has been recognized as a key risk factor for multiple metabolic disorders, including diabetes, cardiovascular diseases and many types of cancer. Herbal medicines have been frequently used for preventing and treating obesity in many countries, but in most cases, the key anti-obesity constituents in herbs and their anti-obesity mechanisms are poorly understood. This study demonstrated a case study for uncovering the anti-obesity constituents in an anti-obesity herbal medicine (Ginkgo biloba extract) and deciphering their synergistic effects via targeting human pancreatic lipase (hPL). Following screening the anti-hPL effects of eighty herbal medicines, Ginkgo biloba extract (GBE50) was found with the most potent anti-hPL activity. Global chemical profiling of herbal constituents coupling with hPL inhibition assay revealed that the bioflavonoids and several flavonoids in GBE50 were key anti-hPL constituents. Among all tested thirty-eight constituents, sciadopitysin, bilobetin, quercetin, isoginkgetin, and ginkgetin showed potent anti-hPL effects (IC50 values <2.5 µM). Inhibition kinetic analyses suggested that sciadopitysin, bilobetin, quercetin, isoginkgetin, and ginkgetin acted as non-competitive inhibitors of hPL, with the Ki values were <2 µM. Docking simulations revealed that four bioflavonoids (sciadopitysin, bilobetin, isoginkgetin, and ginkgetin) could tightly bind on hPL at cavity 2, which it is different from the binding cavity of quercetin on hPL. Further investigations demonstrated that the combinations of quercetin and one bioflavonoid-type hPL inhibitor (sciadopitysin or bilobetin) showed synergistic anti-hPL effects, suggesting that the multi-components in GBE50 may generate more potent anti-hPL effect. Collectively, our findings uncovered the anti-obesity constituents in GBE50, and explored their anti-hPL mechanisms as well as synergistic effects at molecular levels, which will be very helpful for further understanding the anti-obesity mechanisms of Ginkgo biloba.

Screening of sensitive in vivo characteristics for early keratoconus diagnosis: a multicenter study.

Purpose: To analyze and compare sensitive in vivo characteristics for screening early keratoconus. Methods: This multicenter, case-control study included 712 eyes, after matching for age and biomechanically corrected intraocular pressure, from three clinics in different cities. The keratoconus (n = 288), early keratoconus (n = 91), and normal cornea (n = 333) groups included eyes diagnosed with bilateral keratoconus, fellow eyes with relatively normal topography with unilateral keratoconus, and normal eyes before refractive surgery, respectively. After adjusting for central corneal thickness, differences in vivo characteristics were analyzed among the three groups. The in vivo characteristics were measured by Pentacam and Corvis ST. Fifty-four indices were evaluated to screen for a sensitive index for the detection of early keratoconus. Results: Significant differences were observed in 26 of the 36 corneal biomechanical indeces between the early keratoconus and normal corneas. The area under the receiver operating characteristic curve of tomographic and biomechanical index, Belin/Ambrósio deviation, and Da in differentiating keratoconus from normal cornea was 1.000. Among the top five indeces of the area under the receiver operating characteristic curve for detecting early keratoconus, the corneal biomechanical-related index accounted for 80% (4/5), including A1 dArc length, highest concavity radius, A2 time, and tomographic and biomechanical index, of which the area under the receiver operating characteristic curve of A1 dArc length was 0.901. Conclusion: A1 dArc length and several corneal biomechanical indices are highly sensitive for the detection of early keratoconus, even in the absence of topographic abnormalities. Ophthalmologists should focus on the clinical application of corneal biomechanics and combine corneal tomography for the timely and accurate detection of early keratoconus.