Detectability of the potential climate change effect on transboundary air pollution pathways in the downwind area of China.

Long-term aerosol optical depth (AOD) datasets focused on the Pacific Ocean in the downwind area of China over a 19-year period from 2003 to 2021 were derived from satellite observations, reanalysis datasets, and numerical simulations. Considering the significant year-to-year changes in the amounts of aerosols transported from China to the Pacific Ocean during this period, we proposed a metric named RAOD. This is defined as the AOD over the ocean relative to that near the eastern coast of China within the same latitude band (25-30°N). RAOD was identified as a valuable metric for quantifying the long-term changes in transboundary air pollution pathways. Our analysis revealed a clear exponential decrease in RAOD values from China toward the Pacific Ocean; this was consistent with the prevailing meteorological conditions observed over the 19-year period. However, the possible long-term changes in RAOD due to climate change were found to be insignificant and were overshadowed by much larger year-to-year variations in the meteorological field. Additionally, significant seasonal variations in the absolute slope of the linear regression between RAOD and longitude were observed, and there correlated with wind patterns in the lower troposphere. Elevated slope values in the spring and winter suggested a west-to-east aerosol transport facilitated by strong winds, whereas the lower slope values in summer and autumn indicated a northward aerosol movement under weaker winds. In recent years, aerosols have become less likely to be transported far eastward from the coast of China. Based on these findings, to enhance the detectability of the climate change impacts on meteorological field affecting transboundary air pollution pathways, the RAOD metric derived using a continued long-term satellite observation of aerosols is proposed.

Grape seed-derived procyanidins decreases neuropathic pain and nerve regeneration by suppression of toll-like receptor 4-myeloid differentiation factor-88 signaling.

Background: Recent studies have shown that peripheral nerve regeneration process is closely related to neuropathic pain. Toll-like receptor 4 (TLR4) signaling was involved in different types of pain and nerve regeneration. TLR4 induced the recruitment of myeloid differentiation factor-88 adaptor protein (MyD88) and NF-κB-depended transcriptional process in sensory neurons and glial cells, which produced multiple cytokines and promoted the induction and persistence of pain. Our study aimed to investigate procyanidins's effect on pain and nerve regeneration via TLR4-Myd88 signaling. Methods: Spinal nerve ligation (SNL) model was established to measure the analgesic effect of procyanidins. Anatomical measurement of peripheral nerve regeneration was measured by microscopy and growth associated protein 43 (GAP43) staining. Western blotting and/or immunofluorescent staining were utilized to detect TLR4, myeloid differentiation factor-88 adaptor protein (MyD88), ionized calcium-binding adapter molecule 1 (IBA1) and nuclear factor kappa-B-p65 (NF-κB-p65) expression, as well as the activation of astrocyte and microglia. The antagonist of TLR4 (LPS-RS-Ultra, LRU) were intrathecally administrated to assess the behavioral effects of blocking TLR4 signaling on pain and nerve regeneration. Result: Procyanidins reduced mechanical allodynia, thermal hyperalgesia and significantly suppressed the number of nerve fibers regenerated and the degree of myelination in SNL model. Compared with sham group, TLR4, MyD88, IBA1 and phosphorylation of NF-κB-p65 were upregulated in SNL rats which were reversed by procyanidins administration. Additionally, procyanidins also suppressed activation of spinal astrocytes and glial cells. Conclusion: Suppression of TLR4-MyD88 signaling contributes to the alleviation of neuropathic pain and reduction of nerve regeneration by procyanidins.

Dose-response relationship between alcohol drinking and gout risk: do subtypes of alcoholic beverages make a difference?

OBJECTIVE: Although previous studies have explored the association of drinking with gout risk, the dose-response relationship was uncertain and the evidence between subtypes of alcoholic beverages and gout risk was limited. METHODS: The weekly alcoholic beverage consumption in the United Kingdom Biobank (UKB) was collected and calculated. The Cox regression model was applied to assess the impact of alcohol drinking and its subtypes on gout risk by calculating the hazard ratio (HR) and 95% confidence interval (CI). Besides, the restricted cubic splines were used to estimate the dose-response relationship between alcoholic drinking and gout risk. To evaluate the robustness, we performed subgroup analysis across various demographic characteristics. RESULTS: During a mean follow-up period of 11.70 years, a total of 5,728 newly incident gout cases were diagnosed among 331,865 participants. We found that light alcohol drinking was linked to a slight decrease in gout incidence among females (HR, 0.78; 95% CI, 0.65 to 0.94, P=0.01), whereas it showed no significant association in males. Moreover, the dose-response relationship showed that light red wine and fortified wine could reduce the gout risk, while beer, champagne plus white wine and spirits promoted the gout risk at any dose. CONCLUSION: Our study suggested a J-shaped dose-response relationship of drinking with gout risk in females rather than males. For specific alcoholic beverages, light consumption of red wine and fortified wine was associated with reduced gout risk. These findings offer new insights into the roles of alcoholic beverages in gout, while further validation is warranted.

Metabolomics for Clinical Biomarker Discovery and Therapeutic Target Identification.

As links between genotype and phenotype, small-molecule metabolites are attractive biomarkers for disease diagnosis, prognosis, classification, drug screening and treatment, insight into understanding disease pathology and identifying potential targets. Metabolomics technology is crucial for discovering targets of small-molecule metabolites involved in disease phenotype. Mass spectrometry-based metabolomics has implemented in applications in various fields including target discovery, explanation of disease mechanisms and compound screening. It is used to analyze the physiological or pathological states of the organism by investigating the changes in endogenous small-molecule metabolites and associated metabolism from complex metabolic pathways in biological samples. The present review provides a critical update of high-throughput functional metabolomics techniques and diverse applications, and recommends the use of mass spectrometry-based metabolomics for discovering small-molecule metabolite signatures that provide valuable insights into metabolic targets. We also recommend using mass spectrometry-based metabolomics as a powerful tool for identifying and understanding metabolic patterns, metabolic targets and for efficacy evaluation of herbal medicine.

Characteristic abnormal expression of galectin-3 in serrated colon lesions and its pathological significance.

Serrated lesions are precursors of some colon cancers. The expression of galectin-3 has been reported to be involved in BRAF and KRAS mutations (the key pathogenic drivers of serrated lesions). This study aimed to investigate the expression intensity and subcellular localization of galectin-3 in serrated colon lesions by immunohistochemistry. The results demonstrated that, regarding expression intensity, galectin-3 expression in serrated colon lesions was significantly upregulated; regarding subcellular localization, the membrane expression of hyperplastic polyps/ sessile serrated lesions (HP/SSL) was weakened, the structure was disorganized and that of traditional serrated adenoma (TSA) was significantly weakened or disappeared, and the nuclear expression of both was positive; in the dysplasia of SSL (SSL-D) and TSA (TSA-HD), galectin-3 expression intensity remained high, and was weakened or disappeared in some nuclei, the expression disorder of the SSL-D cell membrane was reduced, the polarity of the cell was restored, weak expression appeared in the local cell membrane of TSA-HD, and the "serrated" structure of both was reduced or disappeared and seemed to revert more to that seen in common adenomas. In summary, abnormal galectin-3 expression occurs in the early stages of serrated lesions, its expression is characteristic, the dynamic changes in galectin-3 expression are closely related to the histopathological changes and progression of serrated lesions, and further accumulated molecular alterations contribute to this process.

A novel selenium nanocomposite modified by AANL inhibits tumor growth by upregulating CLK2 in lung cancer.

Lung cancer is a malignant tumor with high mortality and drug resistance. Therefore, it is urgent to explore natural and nontoxic drugs to treat lung cancer. In this study, the natural active ingredient AANL extracted from Agrocybe aegirita was used to modify nanoselenium by an oxidation-reduction method. Transmission electron microscope detection and infrared spectroscopy showed that a novel selenium nanocomposite named AANL-SeNPs was successfully prepared. The results of nanoscale characterization showed that AANL-SeNPs had good stability and uniform dispersion in aqueous solution by zeta potential and spectrum analysis. At the cellular level, we found that AANL-SeNPs significantly inhibited the cell viability of lung cancer cells, and the cell inhibition rate of 60 nM AANL-SeNPs was 39 % in H157 cells, 67 % in H147 cells, and 62 % in A549 cells. The IC50 value of AANL-SeNPs was 51.85 nM in A549 cells and 81.57 nM in H157 cells. Moreover, AANL-SeNPs could inhibit the cell proliferation and migration, and enhance the sensitivity of lung cancer cells to osimertinib and has no toxic to normal cells. In vivo, AANL-SeNPs significantly slowed tumor growth in tumor-bearing mice by establishing a subcutaneous transplantation tumor model for lung cancer, and the tumor size was smaller and was reduced about 79 % in 2 mg/kg AANL-SeNPs group compared with PBS group. Mechanistically, a total of 38 differentially expressed proteins were identified by data-independent acquisition mass spectrometry. A significantly upregulated protein, CDC-like kinase 2 (CLK2), was screened and validated for further analysis, which showed that the expression levels of CLK2 were increased in H157 and H1437 cells after AANL-SeNPs treatment. The results obtained in this study suggest that a novel selenium nanocomposite AANL-SeNPs, which inhibits lung cancer by upregulating the expression of CLK2.

Mechanistic exploration of the Shenlian formula in the suppression of atherosclerosis progression via network pharmacology and in vivo experimental validation.

ETHNOPHARMACOLOGICAL RELEVANCE: The Shenlian formula (SL) is a Chinese medicine formula used to curb the development of atherosclerosis (AS) and cardiovascular disease in clinical practice. However, owing to the complexity of compounds and their related multiple targets in traditional Chinese medicine (TCM), it remains difficult and urgent to elucidate the underlying mechanisms at a holistic level. AIM: To investigate the intrinsic mechanisms by which SL suppresses AS progression and to gain new insight into its clinical use. METHODS: We proposed a network pharmacology-based workflow to evaluate the mechanism by which SL affects AS via data analysis, target prediction, PPI network construction, GO and KEGG analyses, and a "drug-core ingredient-potential target-key pathway" network. Then, non-targeted lipidomic analysis was performed to explore the differential lipid metabolites in AS rats, revealing the possible mechanism by which SL affects atherosclerotic progression. Moreover, an AS rabbit model was constructed and gavaged for SL intervention. Serum lipid profiles and inflammatory cytokine indices were tested as an indication of the mitigating effect of SL on AS. RESULTS: A total of 89 bioactive compounds and 298 targets related to SL and AS, which play essential roles in this process, were identified, and a component-target-disease network was constructed. GO and KEGG analyses revealed that SL regulated metabolic pathway, lipids and atherosclerosis, the PI3K-Akt pathway, the MAPK pathway and so on.In vivo experimental validation revealed that a total of 43 different lipid metabolites regulated by SL were identified by non-targeted lipidomics, and glycerophospholipid metabolism was found to be an important mechanism for SL to interfere with AS. SL reduced the plaque area and decreased the levels of inflammatory cytokines (TNF-α and IL-4) and blood lipids (TC, TG, LDL-C, and ApoB) in HFD-induced AS models. In addition, HDL and ApoA1 levels are increased. PLA2 and Lipin1 are highly expressed in AS model, indicating their role in destabilizing glycerophosphatidylcholine metabolism and contributing to the onset and progression of ankylosing spondylitis. Moreover, SL intervention significantly reduced the level of pro-inflammatory cytokines; significantly down-regulated NF-kB/p65 expression, exhibiting anti-inflammatory activity. CONCLUSION: The Shenlian formula (SL) plays a pivotal role in the suppression of AS progression by targeting multiple pathways and mechanisms. This study provides novel insights into the essential genes and pathways associated with the prognosis and pathogenesis of AS.

TCEB3 initiates ovarian cancer apoptosis by mediating ubiquitination and degradation of MCL-1.

Platinum resistance remains a major contributor to the poor prognosis of ovarian cancer. Anti-apoptotic protein myeloid cell leukemia-1 (MCL-1) has emerged as a promising target for overcoming drug resistance, but different cancer cells utilize distinct protein degradation pathways to alter MCL-1 level. We systematically investigated E3 ligases to identify novel candidates that mediate platinum resistance in ovarian cancer. Transcription Elongation Factor B (TCEB3) has been identified as a novel E3 ligase recognition subunit that targets MCL-1 in the cytoplasm during platinum treatment other than its traditional function of targeting the Pol II in the nuclear compartment. TCEB3 expression is downregulated in platinum-resistant cell lines and this low expression is associated with poor prognosis. The ubiquitination of MCL-1 induced by TCEB3 leads to cell death in ovarian cancer. Moreover, platinum treatment increased the cytoplasm proportion of TCEB3, and the cytoplasm localization of TCEB3 is important for its targeting of MCL-1. This study emphasizes the dual function of TCEB3 in homeostasis maintenance and in cell fate determination under different conditions, and provides a new insight into drug resistance in ovarian cancer.

Succinic Acid Ameliorates Concanavalin A-Induced Hepatitis by Altering the Inflammatory Microenvironment and Expression of BCL-2 Family Proteins.

Autoimmune hepatitis (AIH) is a severe immune-mediated inflammatory liver disease that currently lacks feasible drug treatment methods. Our study aimed to evaluate the protective effect of succinic acid against AIH and provide a reliable method for the clinical treatment of AIH. We performed an in vivo study of the effects of succinic acid on concanavalin A (ConA)-induced liver injury in mice. We examined liver transaminase levels, performed hematoxylin and eosin (HE) staining, and observed apoptotic phenotypes in mice. We performed flow cytometry to detect changes in the number of neutrophils and monocytes, and used liposomes to eliminate the liver Kupffer cells and evaluate their role. We performed bioinformatics analysis, reverse transcription-quantitative polymerase chain reaction (RT-qPCR), and western blotting to detect mitochondrial apoptosis-induced changes in proteins from the B-cell lymphoma 2(Bcl-2) family. Succinic acid ameliorated ConA-induced AIH in a concentration-dependent manner, as reflected in the survival curve. HE and TUNEL staining and terminal deoxynucleotidyl transferase dUTP nick end labeling revealed decreased alanine transaminase and aspartate aminotransferase levels, and reduced liver inflammation and apoptosis. RT-qPCR and enzyme-linked immunosorbent assay revealed that succinic acid significantly reduced liver pro-inflammatory cytokine levels. Flow cytometry revealed significantly decreased levels of liver neutrophils. Moreover, the protective effect of succinic acid disappeared after the Kupffer cells were eliminated, confirming their important role in the effect. Bioinformatics analysis, RT-qPCR, and western blotting showed that succinic acid-induced changes in proteins from the Bcl-2 family involved mitochondrial apoptosis, indicating the molecular mechanism underlying the protective effect of succinic acid. Succinic acid ameliorated ConA-induced liver injury by regulating immune balance, inhibiting pro-inflammatory factors, and promoting anti-apoptotic proteins in the liver. This study provides novel insights into the biological functions and therapeutic potential of succinic acid in the treatment of autoimmune liver injury.

Induction of Petite Colonies in Candida glabrate via Rose Bengal-Mediated Photodynamic Therapy.

Facing a 40% mortality rate in candidemia patients, drug-resistant Candida and their petite mutants remain a major treatment challenge. Antimicrobial photodynamic therapy (aPDT) targets multiple fungal structures, unlike antibiotics/antifungals, potentially thwarting resistance. Traditional methods for inducing petite colonies rely on ethidium bromide or fluconazole, which can influence drug susceptibility and stress responses. This study investigated the application of green light (peak 520 nm) and rose bengal (RB) photosensitizer to combat a drug-resistant Candida glabrata isolate. The findings revealed that aPDT treatment significantly inhibited cell growth (≥99.9% reduction) and effectively induced petite colony formation, as evidenced by reduced size and loss of mitochondrial redox indicator staining. This study provides initial evidence that aPDT can induce petite colonies in a multidrug-resistant C. glabrata strain in vitro, offering a potentially transformative approach for combating resistant fungal infections.

Alleviating Recombinant Tissue Plasminogen Activator-induced Hemorrhagic Transformation in Ischemic Stroke via Targeted Delivery of a Ferroptosis Inhibitor.

Intravenous thrombolysis with recombinant tissue plasminogen activator (rtPA) is the primary treatment for ischemic stroke. However, rtPA treatment can substantially increase blood-brain barrier (BBB) permeability and susceptibility to hemorrhagic transformation. Herein, the mechanism underlying the side effects of rtPA treatment is investigated and demonstrated that ferroptosis plays an important role. The ferroptosis inhibitor, liproxstatin-1 (Lip) is proposed to alleviate the side effects. A well-designed macrocyclic carrier, glucose-modified azocalix[4]arene (GluAC4A), is prepared to deliver Lip to the ischemic site. GluAC4A bound tightly to Lip and markedly improved its solubility. Glucose, modified at the upper rim of GluAC4A, imparts BBB targeting to the drug delivery system owing to the presence of glucose transporter 1 on the BBB surface. The responsiveness of GluAC4A to hypoxia due to the presence of azo groups enabled the targeted release of Lip at the ischemic site. GluAC4A successfully improved drug accumulation in the brain, and Lip@GluAC4A significantly reduced ferroptosis, BBB leakage, and neurological deficits induced by rtPA in vivo. These findings deepen the understanding of the side effects of rtPA treatment and provide a novel strategy for their effective mitigation, which is of great significance for the treatment and prognosis of patients with ischemic stroke.

Fibroblast Growth Factor 23 is a Potential Prognostic Biomarker in Uterine Sarcoma.

BACKGROUND: Uterine sarcoma (US) is a highly malignant cancer with poor prognosis and high mortality in women. In this study, we evaluated the expression of human fibroblast growth factor 23 (FGF23) in different US subtypes and the relationship between survival and clinicopathological characteristics. METHODS: We conducted a comparative analysis of FGF23 gene expression in different pathological types of US. Utilizing a cohort from The Cancer Genome Atlas of 57 patients, a 50-patient microarray dataset (GSE119043) from the Gene Expression Omnibus and a Suining cohort of 44 patients, we analyzed gene expression profiles and corresponding clinicopathological information. Immunohistochemistry was used to examine the expression level of FGF23 in four US subtypes. Survival analysis was used to assess the relationship between FGF23 expression and prognosis in US patients. RESULTS: Compared with uterine normal smooth muscle and uterine leiomyoma, FGF23 expression was significantly upregulated in US and was differentially expressed in four US subtypes. Uterine carcinosarcoma exhibited the highest expression of FGF23 among the subtypes. Survival analysis revealed no correlation between FGF23 expression and either overall survival or progression-free survival in US (P > 0.05). Similar results were obtained from the validation cohorts. Univariate and multivariate analyses showed no significant correlation between FGF23 expression and the US prognosis. Tumor stage, CA125, and tumor recurrence were independent prognostic factors for survival of US patients. CONCLUSION: FGF23 was highly expressed in US and was promising as a novel potential biomarker for the diagnosis and prognosis of US.

Multicomponent comprehensive confirms that erythroferrone is a molecular biomarker of pan-cancer.

All vertebrates organisms produce erythroferrone, a secretory hormone with structure-related functions during iron homeostasis. However, limited knowledge exists regarding the effect of this hormone on the occurrence and progression of cancer. To systematically and comprehensively identify the diverse implications of Erythroferrone (ERFE) in various malignant tumors, we conducted an in-depth analysis of multiple datasets, including the expression levels of oncogenes and target proteins, biological functions, and molecular characteristics. This analysis aimed to assess the diagnostic and prognostic value of ERFE in pan-cancer. Our findings revealed a significant elevation in ERFE expression across 20 distinct cancer types, with notable increases in gastrointestinal cancers. Utilizing the Cytoscape and STRING databases, we identified 35 ERFE-targeted binding proteins. Survival prognosis studies, particularly gastrointestinal cancers indicated by Colon adenocarcinoma (COAD), demonstrated a poor prognosis in patients with high ERFE expression (p < 0.001), consistently observed across various clinical subgroups. Furthermore, the ROC curve underscored the high predictive ability of EFRE for gastrointestinal cancer (AUC >0.9). Understanding the roles and interactions of ERFE in biological processes can also be aided by examining the genes co-expressed with ERFE in the coat and ranking the top 50 positive and negative genes. In the correlation analysis between the ERFE gene and different immune cells in COAD, we discovered that the expression of ERFE was positively correlated with Th1 cells, cytotoxic cells, and activated DC (aDC) abundance, and negatively correlated with Tcm (T central memory) abundance (P < 0.001). in summary, ERFE emerges as strongly associated with various malignant cancers, positioning it as a prospective biological target for cancer treatment. It stands out as a key molecular biomarker for diagnosing and prognosticating pancreatic cancer, also serves as an independent prognostic risk factor for COAD.

Quantitative analysis of the relationship between the myocardial bridge and the FAI of pericoronal fat on computed tomography.

We performed this cohort study to investigate whether the myocardial bridge (MB) affects the fat attenuation index (FAI) and to determine the optimal cardiac phase to measure the volume and the FAI of pericoronary adipose tissue (PCAT). The data of 300 patients who were diagnosed with MB of the left anterior descending (LAD) coronary artery were retrospectively analyzed. All of patients were divided into the MB group and the MB with atherosclerosis group. In addition, 104 patients with negative CCTA results were enrolled as the control group. There was no significant difference between FAI values measured in systole and diastole (P > 0.05). There was no significant difference in FAI among the MB group, the MB with atherosclerosis group, and the control group (P > 0.05). In MB with atherosclerosis group, LAD stenosis degree (< 50%) (OR = 0.186, 95% CI 0.036-0.960; P = 0.045) and MB located in the distal part of LAD opening (OR = 0.880, 95% CI 0.789-0.980; P = 0.020) were protective factors of FAI value. A distance (from the LAD opening to the proximal point of the MB) of 29.85 mm had the highest predictive value for abnormal FAI [area under the curve (AUC), 0.798], with a sensitivity of 81.1% and a specificity of 74.6%.

Cardiac computed tomography angiography-derived pulmonary vein volumetry as a predictor for atrial fibrillation recurrence after catheter ablation.

Background: There is an increasing evidence that pulmonary vein (PV) enlargement is associated with atrial fibrillation (AF); however, the predictive value of PV enlargement in AF recurrence remains unclear. This study sought to evaluate whether PV volume quantification derived from cardiac computed tomographic angiography (CCTA) could serve as a predictive indicator of the success of the catheter ablation (CA) procedure. Methods: The data of 160 patients diagnosed with AF who underwent both CCTA and CA treatments from January to June 2020 were retrospectively examined; the CCTA was conducted before the CA surgery. The study focused on documenting the PV structure, and the volume of the PV and left atrium (LA). The clinical, CCTA, and echocardiographic predictors of the recurrence and no-recurrence groups were compared. A multivariable logistic regression analysis was performed to adjust for confounders. Receiver operating characteristic (ROC) curves were analyzed to assess the predictive performance of the predictors of AF recurrence. Results: Of the 160 patients [55.6% male, 62.00 (55.25-68.00) years, 23.1% with persistent AF], 45 (28.1%) experienced AF recurrence within a one-year period. Notably, patients with AF recurrence had elevated CHADS2 scores (P=0.020) and increased LA and PV volumes (P<0.05). Patients with persistent AF (n=37) had significantly larger LA volume indexes (P<0.001) than those with paroxysmal AF, but there was no difference between the two groups in terms of the PV maximum volume index (P=0.200). Moreover, the PV maximum volume index [odds ratio (OR): 1.244, 95% confidence interval (CI): 1.008-1.536, P=0.042] and the LA minimum volume index (OR: 1.026, 95% CI: 1.001-1.052, P=0.038) were found to be significant predictors of AF recurrence. The ROC curves revealed that the PV maximum volume index threshold for predicting AF recurrence was 7.13 mL/m2, with a sensitivity of 84.4% and a specificity of 34.8% [area under the curve (AUC): 0.635, 95% CI: 0.540-0.730, P=0.008], and the LA minimum volume index threshold for predicting AF recurrence was 46.16 mL/m2, with a sensitivity of 88.9% and a specificity of 31.3% (AUC: 0.629, 95% CI: 0.534-0.723, P=0.012). A sub-analysis of patients with a lower left atrial dimension (LAD ≤38 mm in females, LAD ≤40 mm in males, n=120) demonstrated that the PV maximum volume index was a noteworthy indicator of AF recurrence (OR: 1.443: 95% CI: 1.145-1.820, P=0.002). Conversely, no significant correlation between AF recurrence and the LA volume index was found. The AUC value for the PV maximum volume index predictive of recurrent AF was 0.680 (95% CI: 0.577-0.781, P=0.003), with a sensitivity of 75.8%, specificity of 54%, and the cut-off value of the maximum AUC was 7.89 mL/m2. Conclusions: PV volume, derived from CCTA, may help to predict the recurrence of AF after CA, and is superior to the LA size in patients with less pronounced LA enlargement.

Assembly and analysis of the genome of Notholithocarpus densiflorus.

Tanoak (Notholithocarpus densiflorus) is an evergreen tree in the Fagaceae family found in California and southern Oregon. Historically, tanoak acorns were an important food source for Native American tribes, and the bark was used extensively in the leather tanning process. Long considered a disjunct relictual element of the Asian stone oaks (Lithocarpus spp.), phylogenetic analysis has determined that the tanoak is an example of convergent evolution. Tanoaks are deeply divergent from oaks (Quercus) of the Pacific Northwest and comprise a new genus with a single species. These trees are highly susceptible to "sudden oak death" (SOD), a plant pathogen (Phytophthora ramorum) that has caused widespread deaths of tanoaks. In this study, we set out to assemble the genome and perform comparative studies among a number of individuals that demonstrated varying levels of susceptibility to SOD. First, we sequenced and de novo assembled a draft reference genome of N. densiflorus using cobarcoded library processing methods and an MGI DNBSEQ-G400 sequencer. To increase the contiguity of the final assembly, we also sequenced Oxford Nanopore long reads to 30× coverage. To our knowledge, the draft genome reported here is one of the more contiguous and complete genomes of a tree species published to date, with a contig N50 of ∼1.2 Mb, a scaffold N50 of ∼2.1 Mb, and a complete gene score of 95.5% through BUSCO analysis. In addition, we sequenced 11 genetically distinct individuals and mapped these onto the draft reference genome, enabling the discovery of almost 25 million single nucleotide polymorphisms and ∼4.4 million small insertions and deletions. Finally, using cobarcoded data, we were able to generate a complete haplotype coverage of all 11 genomes.

Proinsulin folding and trafficking defects trigger a common pathological disturbance of endoplasmic reticulum homeostasis.

Primary defects in folding of mutant proinsulin can cause dominant-negative proinsulin accumulation in the endoplasmic reticulum (ER), impaired anterograde proinsulin trafficking, perturbed ER homeostasis, diminished insulin production, and ß-cell dysfunction. Conversely, if primary impairment of ER-to-Golgi trafficking (which also perturbs ER homeostasis) drives misfolding of nonmutant proinsulin-this might suggest bi-directional entry into a common pathological phenotype (proinsulin misfolding, perturbed ER homeostasis, and deficient ER export of proinsulin) that can culminate in diminished insulin storage and diabetes. Here, we've challenged ß-cells with conditions that impair ER-to-Golgi trafficking, and devised an accurate means to assess the relative abundance of distinct folded/misfolded forms of proinsulin using a novel nonreducing SDS-PAGE/immunoblotting protocol. We confirm abundant proinsulin misfolding upon introduction of a diabetogenic INS mutation, or in the islets of db/db mice. Whereas blockade of proinsulin trafficking in Golgi/post-Golgi compartments results in intracellular accumulation of properly-folded proinsulin (bearing native disulfide bonds), impairment of ER-to-Golgi trafficking (regardless whether such impairment is achieved by genetic or pharmacologic means) results in decreased native proinsulin with more misfolded proinsulin. Remarkably, reversible ER-to-Golgi transport defects (such as treatment with brefeldin A or cellular energy depletion) upon reversal quickly restore the ER folding environment, resulting in the disappearance of pre-existing misfolded proinsulin while preserving proinsulin bearing native disulfide bonds. Thus, proper homeostatic balance of ER-to-Golgi trafficking is linked to a more favorable proinsulin folding (as well as trafficking) outcome.

The role of peripheral inflammation-related biomarkers in distinguishing Parkinson's disease.

BACKGROUND: Peripheral inflammation plays a significant role in Parkinson's disease (PD). Conflicting studies on whether inflammatory indicators in blood could serve as biomarkers to distinguish PD. OBJECTIVE: Include a wider range of biomarkers and control confounding factors to comprehensively evaluate the value of peripheral inflammation-related indicators. METHODS: A total of 80 PD patients were recruited and 80 one-to-one matched healthy controls (HCs). The levels of B-cell, T-cell, and natural killer (NK)-cell in blood were measured using flow cytometry. The levels of neurodegeneration-related proteins in serum were detected and clinical blood test results were collected. Multivariable logistic regression analysis was conducted to explore the role of significant variables in PD. Receiver operating characteristic curve analysis was performed to assess the potential value of these variables. RESULTS: Compared to HCs, PD patients showed lower levels of lymphocyte, B-cell, T-cell, high-density lipoprotein cholesterol (HDL-C) and lymphocyte-to-monocyte ratio, while the levels of neutrophil, NK-cell, ß-amyloid40, neurofilament light chain, neutrophil-to-lymphocyte ratio, and neutrophil-to-HDL-C ratio (NHR) were increased. A higher B-cell count was associated with a lower risk of PD, while higher levels of NK-cell and NHR were associated with a higher risk of PD. B-cell, NK-cell and NHR have potential value in distinguishing PD from non-PD. B-cell and NHR levels were significantly correlated with PD dyskinesia scores. CONCLUSIONS: B-cell, NK-cell, and NHR may potentially contribute to distinguishing PD patients from HCs. There could be a correlation between the number of B-cell, the level of NHR, and the severity of PD dyskinesia.

Deep learning using contrast-enhanced ultrasound images to predict the nuclear grade of clear cell renal cell carcinoma.

PURPOSE: To assess the effectiveness of a deep learning model using contrastenhanced ultrasound (CEUS) images in distinguishing between low-grade (grade I and II) and high-grade (grade III and IV) clear cell renal cell carcinoma (ccRCC). METHODS: A retrospective study was conducted using CEUS images of 177 Fuhrmangraded ccRCCs (93 low-grade and 84 high-grade) from May 2017 to December 2020. A total of 6412 CEUS images were captured from the videos and normalized for subsequent analysis. A deep learning model using the RepVGG architecture was proposed to differentiate between low-grade and high-grade ccRCC. The model's performance was evaluated based on sensitivity, specificity, positive predictive value, negative predictive value and area under the receiver operating characteristic curve (AUC). Class activation mapping (CAM) was used to visualize the specific areas that contribute to the model's predictions. RESULTS: For discriminating high-grade ccRCC from low-grade, the deep learning model achieved a sensitivity of 74.8%, specificity of 79.1%, accuracy of 77.0%, and an AUC of 0.852 in the test set. CONCLUSION: The deep learning model based on CEUS images can accurately differentiate between low-grade and high-grade ccRCC in a non-invasive manner.