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.

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.

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.

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.

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.

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.

Integrated Electrochemical Aptasensor Array toward Monitoring Anticancer Drugs in Sweat.

In the realm of clinical practice, the concurrent utilization of anticancer medications can enhance their overall therapeutic efficacy. However, it is crucial to acknowledge that the interactions among these anticancer drugs can potentially yield detrimental consequences on their intended outcomes. Consequently, the assessment of both anticancer potency and potential toxic side effects is greatly refined when multiple anticancer drugs are simultaneously detected and evaluated. Here, we designed a wearable electrochemical aptasensor array for monitoring multiple anticancer drugs in sweat. The integrated sensor array consists of three working electrodes modified with three different aptamers (Apt1, Apt2, and Apt3), a Au counter electrode, and a Ag/AgCl reference electrode. Molecular docking simulations were performed to show the binding affinities between three anticancer drugs and their corresponding aptamers. Various eigenvalues were derived from the square-wave voltammetry electrochemical signals, and these data sets were subjected to rigorous analysis through multivariate data analysis techniques. This analytical approach demonstrated exceptional performance by achieving flawless 100% accuracy in the precise identification of nine anticancer drugs consistently at uniform concentrations. Furthermore, the integrated wearable sensor array exhibited impressive capabilities, correctly recognizing all nine anticancer drugs with 100% accuracy and successfully distinguishing between these drugs in artificial sweat samples. The proposed sensor array presents good stability for 15 days. Flexibility tests showed stable device performance after 500 twisting cycles. This innovative wearable sensing array represents a novel approach for achieving real-time monitoring and precise adjustment of drug dosages. It offers invaluable insights for tailoring the treatment of anticancer drugs to individual patients, predicting both drug efficacy and potential adverse reactions within the field of clinical medicine.

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 mortality of tanoaks. Here, 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 co-barcoded library processing methods and an MGI DNBSEQ-G400 sequencer. To increase the contiguity of the final assembly, we also sequenced Oxford Nanopore (ONT) long reads to 30X 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 co-barcoded data we were able to generate complete haplotype coverage of all 11 genomes.

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%.

Quantitative computed tomography angiography evaluation of the coronary fractional flow reserve in patients with left anterior descending artery myocardial bridging.

PURPOSE: To quantitatively investigate the effect of myocardial bridge (MB) in the left anterior descending artery (LAD) on the fractional flow reserve (FFR). MATERIALS AND METHODS: Three-hundred patients with LAD MB who had undergone coronary artery CT angiography (CCTA) were retrospectively enroled, and 104 normal patients were enroled as the control. The CCTA-derived fractional flow reserve (FFRCT) was measured at the LAD 10 mm proximal (FFR1) and 20-40 mm distal (FFR3) to the MB and at the MB location (FFR2). RESULTS: FFR2 and FFR3 of the MB (with BM only) and MBLA (with both MB and atherosclerosis) groups were significantly (p < 0.01) lower than those of the control. The FFR3 distal to the MB was significantly lower (p < 0.01) than that of the control. The FFRCT of the whole LAD in the MBLA group was significantly (p < 0.05) lower than that of the MB and control group (p < 0.05). MB length (OR 1.061) and MB muscle index (odds ratio or OR 1.007) were two risk factors for abnormal FFRCT, and MB length was a significant independent risk factor for abnormal FFRCT (OR = 1.077). LAD stenosis degree was a risk factor for abnormal FFRCT values (OR 3.301, 95% confidence interval [CI] 1.441-7.562, p = 0.005) and was also a significant independent risk factor (OR = 3.369, 95% CI: 1.392-8.152; p = 0.007) for abnormal FFRCT. CONCLUSION: MB significantly affects the FFRCT of distal coronary artery. For patients with MB without atherosclerosis, the MB length is a risk factor significantly affecting FFRCT, and for patients with MB accompanied by atherosclerosis, LAD stenotic severity is an independent risk factor for FFRCT.

Clinical characteristics of acute acquired concomitant esotropia before and after the COVID-19 pandemic: a retrospective analysis.

PURPOSE: This study aimed to observe the clinical characteristics of acute acquired concomitant esotropia (AACE) patients in recent five years and to examine the changes in the proportion of AACE cases before and after the COVID-19 pandemic. METHODS: A retrospective study included 148 patients who underwent strabismus correction surgery for AACE between January 1, 2017, and December 31, 2021. The study analyzed the changing proportion of AACE cases before and after the COVID-19 pandemic and analyzed its clinical characteristics. RESULTS: Abnormalities in the worth 4 dot examination (both distance and near) were present in 134 cases (90.54%) before surgery, while 140 cases (94.59%) showed normal results after surgery. Near stereoacuity was present in 135 cases (91.22%). The near and distance deviations were (55.01 ± 18.77) PD and (57.30 ± 17.64) PD, respectively, and there was no significant difference between the two (p = 0.279). There were significant differences in the ratio of refractive status among different age groups (p < 0.001), while no statistically significant difference was observed in the ratio of refractive status for near deviation (p = 0.085) or distance deviation (p = 0.116). The proportion of AACE cases after the COVID-19 pandemic was significantly higher than that before the COVID-19 pandemic (p = 0.042). There was no statistically significant difference in the clinical characteristics between the two groups (p > 0.05). CONCLUSIONS: Myopia is the most common refractive status in AACE. More than half of patients had occupations that involved long hours of close work. The proportion of AACE cases increased significantly after the COVID-19 pandemic.

Rational Design of a Potent Antimicrobial Peptide Based on the Active Region of a Gecko Cathelicidin.

The emergence of multidrug-resistant (MDR) bacteria presents a significant challenge to public health, increasing the risk of infections that are resistant to current antibiotic treatment. Antimicrobial peptides (AMPs) offer a promising alternative to conventional antibiotics in the prevention of MDR bacterial infections. In the present study, we identified a novel cathelicidin AMP from Gekko japonicus, which exhibited broad-spectrum antibacterial activity against both Gram-negative and Gram-positive bacteria, with minimal inhibitory concentrations ranging from 2.34 to 4.69 µg/mL. To improve its potential therapeutic application, a series of peptides was synthesized based on the active region of the gecko-derived cathelicidin. The lead peptide (RH-16) showed an antimicrobial activity comparable to that of the parent peptide. Structural characterization revealed that RH-16 adopted an amphipathic α-helical conformation. Furthermore, RH-16 demonstrated neither hemolytic nor cytotoxic activity but effectively killed a wide range of clinically isolated, drug-resistant bacteria. The antimicrobial activity of RH-16 was attributed to the nonspecific targeting of bacterial membranes, leading to rapid bacterial membrane permeabilization and rupture. RH-16 also retained its antibacterial activity in plasma and exhibited mild toxicity in vivo. Notably, RH-16 offered robust protection against skin infection in a murine model. Therefore, this newly identified cathelicidin AMP may be a strong candidate for future pharmacological development targeting multidrug resistance. The use of a rational design approach for isolating the minimal antimicrobial unit may accelerate the transition of natural AMPs to clinically applicable antibacterial agents.

Adenosine-modulating synthetic high-density lipoprotein for chemoimmunotherapy of triple-negative breast cancer.

Adenosine (ADO) is a common chemotherapy-associated immune checkpoint that hinders anti-tumor immunity-mediated efficacy of chemotherapy. Herein, we created a synthetic high-density lipoprotein (sHDL) by co-assembly of a doxorubicin (DOX)-apolipoprotein A1 mimetic peptide conjugate, PSB-603 (an A2BR inhibitor), phospholipid, and cholesterol oleate with a microfluidic-based method. The obtained DP-sHDL showed a self-promoted drug delivery to cancer cells via remodeling tumor microenvironment. DP-sHDL could trigger the release of ATP from cancer cells and inhibit its conversion into ADO. Consequently, DP-sHDL, while increasing immunogenic cell death, reduced intratumoral ADO levels by 58%. This treatment improved both the density and activity of CD8+ T cells as well as NK cells and relieved the immunosuppressive microenvironment, and led to a substantial inhibition of 4T1 tumor growth, thereby extending the survival of mice. The efficacy of DP-sHDL could be further improved when used in combination with immune checkpoint blockade therapy. We envision that this platform provides a simple yet promising strategy to enhance anti-tumor response of chemotherapy by relieving treatment-associated immunosuppression.

Decoding active compounds and molecular targets of herbal medicine by high-throughput metabolomics technology: A systematic review.

Clinical experiences of herbal medicine (HM) have been used to treat a variety of human intractable diseases. As the treatment of diseases using HM is characterized by multi-components and multi-targets, it is difficult to determine the bio-active components, explore the molecular targets and reveal the mechanisms of action. Metabolomics is frequently used to characterize the effect of external disturbances on organisms because of its unique advantages on detecting changes in endogenous small-molecule metabolites. Its systematicity and integrity are consistent with the effective characteristics of HM. After HM intervention, metabolomics can accurately capture and describe the behavior of endogenous metabolites under the disturbance of functional compounds, which will be used to decode the bioactive ingredients of HM and expound the molecular targets. Metabolomics can provide an approach for explaining HM, addressing unclear clinical efficacy and undefined mechanisms of action. In this review, the metabolomics strategy and its applications in HM are systematically introduced, which offers valuable insights for metabolomics methods to characterizing the pharmacological effects and molecular targets of HM.

An accurate aging clock developed from large-scale gut microbiome and human gene expression data.

Accurate measurement of the biological markers of the aging process could provide an "aging clock" measuring predicted longevity and enable the quantification of the effects of specific lifestyle choices on healthy aging. Using machine learning techniques, we demonstrate that chronological age can be predicted accurately from (1) the expression level of human genes in capillary blood and (2) the expression level of microbial genes in stool samples. The latter uses a very large metatranscriptomic dataset, stool samples from 90,303 individuals, which arguably results in a higher quality microbiome-aging model than prior work. Our analysis suggests associations between biological age and lifestyle/health factors, e.g., people on a paleo diet or with IBS tend to have higher model-predicted ages and people on a vegetarian diet tend to have lower model-predicted ages. We delineate the key pathways of systems-level biological decline based on the age-specific features of our model.