Annexin A1 induces oxaliplatin resistance of gastric cancer through autophagy by targeting PI3K/AKT/mTOR.

Resistance to oxaliplatin (OXA) is a major cause of recurrence in gastric cancer (GC) patients. Autophagy is an important factor ensuring the survival of cancer cells under chemotherapeutic stress. We aimed to investigate the role of OXA-related genes in autophagy and chemoresistance of gastric cancer cells. We established OXA-resistant gastric cancer cells and used RNA-seq to profile gene expression within OXA-resistant GC and corresponding parental cells. Immunohistochemistry and RT-qPCR was performed to detect gene expression in tissues of two cohorts of GC patients who received OXA-based chemotherapy. The chemoresistant effects of the gene were assessed by cell viability, apoptosis, and autophagy assays. The effects of the gene on autophagy were assessed with mRFP-GFP-LC3 and Western blotting (WB). Gene set enrichment analysis (GSEA) and WB were performed to detect the activity of PI3K/AKT/mTOR signaling under the regulation of the gene. The OXA-resistant property of GC cells is related to their enhanced autophagic activity. Based on RNA-seq profiling, ANXA1 was selected as a candidate, as it was upregulated significantly in OXA-resistant cells. Furthermore, we found that higher ANXA1 expression before chemotherapy was associated with subsequent development of resistance to oxaliplatin, and overexpression of ANXA1 promoted the resistance of gastric cancer cells to oxaliplatin. So, it may serve as a key regulator in GC chemo-resistance knockdown of ANXA1, via inhibiting autophagy, enhancing the sensitivity of OXA-resistant GC cells to OXA in vitro and in vivo. Mechanically, we identified that PI3K/AKT/mTOR signaling pathway was activated in the ANXA1 stable knockdown AGS/OXA cells, which leads to the suppression of autophagy. ANXA1 functions as a chemoresistant gene in GC cells by targeting the PI3K/AKT/mTOR signaling pathway and might be a prognostic predictor for GC patients who receive OXA-based chemotherapy.

Triboelectric Nanogenerators: State of the Art.

The triboelectric nanogenerator (TENG), as a novel energy harvesting technology, has garnered widespread attention. As a relatively young field in nanogenerator research, investigations into various aspects of the TENG are still ongoing. This review summarizes the development and dissemination of the fundamental principles of triboelectricity generation. It outlines the evolution of triboelectricity principles, ranging from the fabrication of the first TENG to the selection of triboelectric materials and the confirmation of the electron cloud overlapping model. Furthermore, recent advancements in TENG application scenarios are discussed from four perspectives, along with the research progress in performance optimization through three primary approaches, highlighting their respective strengths and limitations. Finally, the paper addresses the major challenges hindering the practical application and widespread adoption of TENGs, while also providing insights into future developments. With continued research on the TENG, it is expected that these challenges can be overcome, paving the way for its extensive utilization in various real-world scenarios.

Damage Detection for Rotating Blades Using Digital Image Correlation with an AC-SURF Matching Algorithm.

The motion information of blades is a key reflection of the operation state of an entire wind turbine unit. However, the special structure and operation characteristics of rotating blades have become critical obstacles for existing contact vibration monitoring technologies. Digital image correlation performs powerfully in non-contact, full-field measurements, and has increasingly become a popular method for solving the problem of rotating blade monitoring. Aiming at the problem of large-scale rotation matching for blades, this paper proposes a modified speeded-up robust features (SURF)-enhanced digital image correlation algorithm to extract the full-field deformation of blades. Combining an angle compensation (AC) strategy, the AC-SURF algorithm is developed to estimate the rotation angle. Then, an iterative process is presented to calculate the accurate rotation displacement. Subsequently, with reference to the initial state of rotation, the relative strain distribution caused by flaws is determined. Finally, the sensitivity of the strain is validated by comparing the three damage indicators including unbalanced rotational displacement, frequency change, and surface strain field. The performance of the proposed algorithm is verified by laboratory tests of blade damage detection and wind turbine model deformation monitoring. The study demonstrated that the proposed method provides an effective and robust solution for the operation status monitoring and damage detection of wind turbine blades. Furthermore, the strain-based damage detection algorithm is more advantageous in identifying cracks on rotating blades than one based on fluctuated displacement or frequency change.

Enantioselective recognition of tryptophan isomers with molecularly imprinted overoxidized polypyrrole/poly(p-aminobenzene sulfonic acid) modified electrode.

Poly(p-aminobenzene sulfonic acid) (pABSA) was electrodeposited onto the surface of a glassy carbon electrode (GCE), which was then used for the preconcentration of l-tryptophan (l-Trp) due to the electrostatic and π-π interactions between pABSA and l-Trp. Polypyrrole (PPy) was electrodeposited onto the surface of the l-Trp enriched pABSA, and then the l-Trp templates were removed, resulting in molecularly imprinted PPy/pABSA. To avoid the interference from the oxidation peak of PPy on the following electrochemical chiral recognition of Trp isomers, PPy was overoxidized by cyclic voltammetry (CV). The resultant molecularly imprinted overoxidized PPy (OPPy)/pABSA modified GCE exhibits higher affinity toward l-Trp than d-tryptophan (d-Trp); that is, the oxidation peak current of l-Trp is greatly higher than that of d-Trp at the molecularly imprinted OPPy/pABSA modified GCE.

Subpixel Matching Using Double-Precision Gradient-Based Method for Digital Image Correlation.

Digital image correlation (DIC) for displacement and strain measurement has flourished in recent years. There are integer pixel and subpixel matching steps to extract displacement from a series of images in the DIC approach, and identification accuracy mainly depends on the latter step. A subpixel displacement matching method, named the double-precision gradient-based algorithm (DPG), is proposed in this study. After, the integer pixel displacement is identified using the coarse-fine search algorithm. In order to improve the accuracy and anti-noise capability in the subpixel extraction step, the traditional gradient-based method is used to analyze the data on the speckle patterns using the computer, and the influence of noise is considered. These two nearest integer pixels in one direction are both utilized as an interpolation center. Then, two subpixel displacements are extracted by the five-point bicubic spline interpolation algorithm using these two interpolation centers. A novel combination coefficient considering contaminated noises is presented to merge these two subpixel displacements to obtain the final identification displacement. Results from a simulated speckle pattern and a painted beam bending test show that the accuracy of the proposed method can be improved by four times that of the traditional gradient-based method that reaches the same high accuracy as the Newton-Raphson method. The accuracy of the proposed method efficiently reaches at 92.67%, higher than the Newton-Raphon method, and it has better anti-noise performance and stability.

Single Neural Adaptive PID Control for Small UAV Micro-Turbojet Engine.

The micro-turbojet engine (MTE) is especially suitable for unmanned aerial vehicles (UAVs). Because the rotor speed is proportional to the thrust force, the accurate speed tracking control is indispensable for MTE. Thanks to its simplicity, the proportional-integral-derivative (PID) controller is commonly used for rotor speed regulation. However, the PID controller cannot guarantee superior performance over the entire operation range due to the time-variance and strong nonlinearity of MTE. The gain scheduling approach using a family of linear controllers is recognized as an efficient alternative, but such a solution heavily relies on the model sets and pre-knowledge. To tackle such challenges, a single neural adaptive PID (SNA-PID) controller is proposed herein for rotor speed control. The new controller featuring with a single-neuron network is able to adaptively tune the gains (weights) online. The simple structure of the controller reduces the computational load and facilitates the algorithm implementation on low-cost hardware. Finally, the proposed controller is validated by numerical simulations and experiments on the MTE in laboratory conditions, and the results show that the proposed controller achieves remarkable effectiveness for speed tracking control. In comparison with the PID controller, the proposed controller yields 54% and 66% reductions on static tracking error under two typical cases.

Correction to: SPECT/CT imaging of apoptosis in aortic aneurysm with radiolabeled duramycin.

The original version of this article unfortunately contains errors in Figure 4. An incorrect Figure 4D is published which is actually a repetition of Figure 2C (i.e., apoptosis rate in control vs. H2O2-treated group). The correct Figure 4D should be the aortic diameter of control vs. experimental groups. Also, the order of part figures (a\b\c\d) in Figure 4E is incorrect. The correct Figure 4 is given below.

SPECT/CT imaging of apoptosis in aortic aneurysm with radiolabeled duramycin.

The objective of this research was to estimate whether a [99mTc]duramycin probe can be used for apoptosis imaging in patients with aortic aneurysm (AA). Vascular smooth muscle cell (SMC) apoptosis has an important influence on AA development. Thus, non-invasive imaging of SMC apoptosis may be able to evaluate AA progress and risk stratification. SMCs were treated with hydrogen peroxide (H2O2; 200 µΜ) or culture medium as a control. Apoptosis was measured using flow cytometry and [99mTc]duramycin to detect the binding efficiency to apoptotic SMCs. C57/BL6 mice were administered angiotensin-II and beta-aminopropionitrile (BAPN) subcutaneously to establish an AA model, or saline for controls. Aortic specimens underwent pathological evaluation and their aortic diameters were measured after 6 weeks. Micro-SPECT/CT scanning of [99mTc]duramycin and 18F-FDG PET detection were performed. SMCs treated with H2O2 showed more apoptosis compared with the control group (67.2 ± 3.8% vs. 16.1 ± 0.6%, P < 0.01). The experimental group showed a high rate of AA formation (70%) compared with no AA formation in the control group. The average aorta diameter was higher and [99mTc]duramycin uptake at the AA site was higher in the experimental group compared with the control group. Compared with the normal aorta in the control group, AA in experiment group had more severe medial degeneration, elastic fiber reduction and fracture, and collagen degeneration. TUNEL staining verified the higher apoptosis rate at the AA site in experiment group compared with the control group (63.9 ± 3.7% in ascending AA, 66.4 ± 4.0% in thoracic AA, vs. 3.5 ± 0.3% in normal aorta, P < 0.01). [99mTc]Duramycin may be an effective probe to evaluate apoptosis in AA.

An An Open-Label, Single Center, Retrospective Study to Evaluate Clinical Outcomes with Surgical Sealant in Bentall Procedures: A Cohort Study.

BACKGROUND: Cardiovascular surgery is associated with substantial risk for postoperative bleeding with increased patient morbidity and mortality. Numerous intraoperative techniques have been utilized to reduce this risk. This study was to assess postoperative bleeding-related parameters following Bentall procedures and to examine the impact of intraoperative surgical sealant application. METHOD: The medical/surgical records of 100 consecutive Bentall procedure cases were examined retrospectively for perioperative surgical sealant use and postoperative bleeding-related outcomes. RESULTS: Of the 100 patient cases, three died during the postoperative period, and 97 were evaluable. Surgical sealant was utilized in 56 patient cases (57.8%). The utilization versus no utilization of surgical sealant was associated with significant reductions in most postoperative bleeding-related parameters, including less drainage (P = .028), resternotomy for hemorrhage (P = .036), transfusion of red blood cells (P = .022 at 48 hours; P = .027 total in-hospital), transfusion of fresh frozen plasma (P = .04 at 48 hours; P = .004 total in-hospital), and a higher percentage of cases not needing blood transfusion (P = .002). The surgical sealant group had longer cardiopulmonary bypass circuit (P = .016) and aortic cross-clamp time (P = .001), with no significant between-group differences in intubation time (P = .636) or intensive care unit duration (P = .294). When excluding urgent cases or Stanford type A aortic dissections, intensive care unit duration significantly was shorter in the surgical sealant group (P = .017). Surgical sealant use was not associated with any adverse events. CONCLUSION: The application of surgical sealant to the anastomosis suture line in Bentall procedures reduces postoperative drainage, bleeding, and transfusion utilization. Further studies are warranted to investigate these benefits in prospective, randomized clinical trials.

Impact of Presurgical Mild Acute Respiratory Distress Syndrome on Surgical Mortality After Surgical Repair of Acute Type A Aortic Dissection.

To evaluate the impact of presurgical mild acute respiratory distress syndrome (ARDS) on surgical mortality in patients undergoing surgical repair of acute type A aortic dissection by means of deep hypothermic circulatory arrest (DHCA) in a single-center, retrospective study.From January 2011 to December 2015, 333 eligible patients were divided into either a mild-ARDS group (n = 136) or a no-ARDS group (n = 197). The definition of mild ARDS referred to the recent revision of ARDS definition (Berlin criteria). The surgical mortality and major postoperative morbidity were investigated and analyzed.A total of 136 patients developed presurgical mild ARDS, with an incidence of 40.8%. No significant difference emerged between the 2 groups in major postoperative morbidity except for pulmonary complications. Multivariate logistic regression displayed that the risk of postoperative pulmonary complications in patients with presurgical mild ARDS was 4.25 times that in patients without presurgical ARDS (OR = 4.25, 95% CI 2.05-7.72). Twenty-four patients died after surgery, with significantly higher surgical mortality in the mild-ARDS group compared with the no-ARDS group (12.5% versus 3.6%, P = 0.002). Kaplan-Meier curves showed a poor surgical survival in the mild-ARDS group (χ2=12.958, Log-Rank P < 0.001). And Cox regression revealed the hazard ratio for surgical mortality in the mild-ARDS group compared with the no-ARDS group was 2.52 (95%CI 1.41-5.32, P = 0.016).Presurgical mild ARDS increased postoperative respiratory morbidity, and then increased surgical mortality after surgical repair of acute type A aortic dissection by means of DHCA.

Complementary interactions between command-like interneurons that function to activate and specify motor programs.

Motor activity is often initiated by a population of command-like interneurons. Command-like interneurons that reliably drive programs have received the most attention, so little is known about how less reliable command-like interneurons may contribute to program generation. We study two electrically coupled interneurons, cerebral-buccal interneuron-2 (CBI-2) and CBI-11, which activate feeding motor programs in the mollusk Aplysia californica. Earlier work indicated that, in rested preparations, CBI-2, a powerful activator of programs, can trigger ingestive and egestive programs. CBI-2 reliably generated ingestive patterns only when it was repeatedly stimulated. The ability of CBI-2 to trigger motor activity has been attributed to the two program-promoting peptides it contains, FCAP and CP2. Here, we show that CBI-11 differs from CBI-2 in that it contains FCAP but not CP2. Furthermore, it is weak in its ability to drive programs. On its own, CBI-11 is therefore less effective as a program activator. When it is successful, however, CBI-11 is an effective specifier of motor activity; that is, it drives mostly ingestive programs. Importantly, we found that CBI-2 and CBI-11 complement each other's actions. First, prestimulation of CBI-2 enhanced the ability of CBI-11 to drive programs. This effect appears to be partly mediated by CP2. Second, coactivation of CBI-11 with CBI-2 makes CBI-2 programs immediately ingestive. This effect may be mediated by specific actions that CBI-11 exerts on pattern-generating interneurons. Therefore, different classes of command-like neurons in a motor network may make distinct, but potentially complementary, contributions as either activators or specifiers of motor activity.

Exploring pollution control in transboundary watersheds under the perspective of ecological compensation based on aggregate game.

Pollution control in inter-provincial river basins involves many complex subjects, so it is difficult to effectively implement ecological compensation policies. To clarify the interest relationship among pollution control subjects and stimulate their willingness to cooperate in collaborative governance, this paper builds a multi-agent coordinated pollution control model based on the theory of aggregate game; explores the change of equilibrium action of a single pollution control agent and multi-actors, symmetric, and asymmetric situations under the influence of synergistic benefits; and studies the incentive mechanism design to maintain the cooperation of various agents. The research results show that an increase in the number of upstream firms would lead to a reduction in the incentive effects of downstream government compensation and an increase in the likelihood of "free-riding" and "coordination failure." Synergy benefits vary positively with the degree of cooperation between government and enterprises, and higher synergy benefits can effectively compensate for the high transaction costs caused by multiple entities, alleviate the financial pressure on downstream governments, and increase the willingness of upstream and downstream entities to cooperate. In addition, focusing on wastewater reduction from core enterprises, such as heavy polluters can help improve the efficiency of regional emissions reduction, while having a catalytic effect on small enterprises.

Mixing with native broadleaf trees modified soil microbial communities of Cunninghamia lanceolata monocultures in South China.

Mixing with different broadleaf trees into the monocultures of Cunninghamia lanceolata is widely adopted as an efficient transformation of the pure C. lanceolata forest. However, it is unclear how native broad-leaved trees influence the belowground ecological environment of the pure C. lanceolata culture plantation in nutrient-poor soil of South China. Herein, we aimed to investigate how a long-time mixing with native broadleaf trees shape soil microbial community of the pure C. lanceolata forest across different soil depth (0-20 cm and 20-40 cm) and to clarify relationships between the modified soil microbial community and those affected soil chemical properties. Using high-throughput sequencing technology, microbial compositions from the mixed C. lanceolata-broadleaf forest and the pure C. lanceolata forest were analyzed. Network analysis was utilized to investigate correlations among microorganisms, and network robustness was assessed by calculating network natural connectivity. Results demonstrated that the content of soil microbial biomass carbon and nitrogen, total phosphorus and pH in mixed forest stand were significantly higher than those in pure forest stand, except for available phosphorus in topsoil (0-20 cm). Simultaneously, the mixed C. lanceolata-broadleaf forest has a more homogeneous bacterial and fungal communities across different soil depth compared with the pure C. lanceolata forest, wherein the mixed forest recruited more diverse bacterial community in subsoil (20-40 cm) and reduced the diversity of fungal community in topsoil. Meanwhile, the mixed forest showed higher bacterial community stability while the pure forest showed higher fungal community stability. Moreover, bacterial communities showed significant correlations with various soil chemical indicators, whereas fungal communities exhibited correlations with only TP and pH. Therefore, the mixed C. lanceolata-broadleaf forest rely on their recruiting bacterial community to enhance and maintain the higher nutrient status of soil while the pure C. lanceolata forest rely on some specific fungi to satisfy their phosphorus requirement for survive strategy.

The fatty acid-related gene signature stratifies poor prognosis patients and characterizes TIME in cutaneous melanoma.

BACKGROUND: The aim of this study is to build a prognostic model for cutaneous melanoma (CM) using fatty acid-related genes and evaluate its capacity for predicting prognosis, identifying the tumor immune microenvironment (TIME) composition, and assessing drug sensitivity. METHODS: Through the analysis of transcriptional data from TCGA-SKCM and GTEx datasets, we screened for differentially expressed fatty acids-related genes (DEFAGs). Additionally, we employed clinical data from TCGA-SKCM and GSE65904 to identify genes associated with prognosis. Subsequently, utilizing all the identified prognosis-related fatty acid genes, we performed unsupervised clustering analysis using the ConsensusClusterPlus R package. We further validated the significant differences between subtypes through survival analysis and pathway analysis. To predict prognosis, we developed a LASSO-Cox prognostic signature. This signature's predictive ability was rigorously examined through multivariant Cox regression, survival analysis, and ROC curve analysis. Following this, we constructed a nomogram based on the aforementioned signature and evaluated its accuracy and clinical utility using calibration curves, cumulative hazard rates, and decision curve analysis. Using this signature, we stratified all cases into high- and low-risk groups and compared the differences in immune characteristics and drug treatment responsiveness between these two subgroups. Additionally, in this study, we provided preliminary confirmation of the pivotal role of CD1D in the TIME of CM. We analyzed its expression across various immune cell types and its correlation with intercellular communication using single-cell data from the GSE139249 dataset. RESULTS: In this study, a total of 84 DEFAGs were identified, among which 18 were associated with prognosis. Utilizing these 18 prognosis-related genes, all cases were categorized into three subtypes. Significant differences were observed between subtypes in terms of survival outcomes, the expression of the 18 DEFAGs, immune cell proportions, and enriched pathways. A LASSO-Cox regression analysis was performed on these 18 genes, leading to the development of a signature comprising 6 DEFAGs. Risk scores were calculated for all cases, dividing them into high-risk and low-risk groups. High-risk patients exhibited significantly poorer prognosis than low-risk patients, both in the training group (p < 0.001) and the test group (p = 0.002). Multivariate Cox regression analysis indicated that this signature could independently predict outcomes [HR = 2.03 (1.69-2.45), p < 0.001]. The area under the ROC curve for the training and test groups was 0.715 and 0.661, respectively. Combining risk scores with clinical factors including metastatic status and patient age, a nomogram was constructed, which demonstrated significant predictive power for 3  and 5 years patient outcomes. Furthermore, the high and low-risk subgroups displayed differences in the composition of various immune cells, including M1 macrophages, M0 macrophages, and CD8+ T cells. The low-risk subgroup exhibited higher StromalScore, ImmuneScore, and ESTIMATEScore (p < 0.001) and demonstrated better responsiveness to immune therapy for patients with PD1-positive and CTLA4-negative or positive expressions (p < 0.001). The signature gene CD1D was found to be mainly expressed in monocytes/macrophages and dendritic cells within the TIME. Through intercellular communication analysis, it was observed that cases with high CD1D expression exhibited significantly enhanced signal transductions from other immune cells to monocytes/macrophages, particularly the (HLA-A/B/C/E/F)-CD8A signaling from natural killer (NK) cells to monocytes/macrophages (p < 0.01). CONCLUSIONS: The prognostic signature constructed in this study, based on six fatty acid-related genes, exhibits strong capabilities in predicting patient outcomes, identifying the TIME, and assessing drug sensitivity. This signature can aid in patient risk stratification and provide guidance for clinical treatment strategies. Additionally, our research highlights the crucial role of CD1D in the CM's TIME, laying a theoretical foundation for future related studies.

Unsupervised domain adaptation for Covid-19 classification based on balanced slice Wasserstein distance.

Covid-19 has swept the world since 2020, taking millions of lives. In order to seek a rapid diagnosis of Covid-19, deep learning-based Covid-19 classification methods have been extensively developed. However, deep learning relies on many samples with high-quality labels, which is expensive. To this end, we propose a novel unsupervised domain adaptation method to process many different but related Covid-19 X-ray images. Unlike existing unsupervised domain adaptation methods that cannot handle conditional class distributions, we adopt a balanced Slice Wasserstein distance as the metric for unsupervised domain adaptation to solve this problem. Multiple standard datasets for domain adaptation and X-ray datasets of different Covid-19 are adopted to verify the effectiveness of our proposed method. Experimented by cross-adopting multiple datasets as source and target domains, respectively, our proposed method can effectively capture discriminative and domain-invariant representations with better data distribution matching.

Tuning pyridinic-N and graphitic-N doping with 4,4'-bipyridine in honeycomb-like porous carbon and distinct electrochemical roles in aqueous and ionic liquid gel electrolytes for symmetric supercapacitors.

Doping engineering in nanostructured carbon materials is an effective approach to modify heteroatom species and surface electronic structures. Herein, an advanced electrode material based on a honeycomb-like porous carbon matrix with tunable N-doped configurations is prepared via 4,4'-bipyridine (4,4'-bpy)-assisted pyrolysis of SiO2@ZIF-8 templates and subsequent etching treatment. Interestingly, the amounts of pyridinic-N and graphitic-N can be controlled by rationally varying the content of 4,4'-bpy which acts as the N source in the pyrolysis process. Both experimental results and density functional theory calculations have revealed that synergistically with 3D interconnected porous architecture, pyridinic-N and graphitic-N have different effects on the electrochemical performances in aqueous and ionic liquid gel electrolytes for symmetric supercapacitors. Highly exposed pyridinic-N endows the carbon electrode with a strengthened pseudocapacitance contribution manifested as a high specific capacitance of 436.1 F g-1 and exceptional stability of almost 100% capacitance retention after 5000 cycles at 10 A g-1 in the KOH/polyvinyl alcohol (PVA) electrolyte. By contrast, graphitic-N is propitious for reinforced electrical double-layer capacitance contribution, reflected by a maximum energy density of 125.4 Wh kg-1 in the 1-ethyl-3-methylimidazolium tetrafluoroborate/poly(vinylidene fluoride-co-hexafluoropropylene) (EMIMBF4/PVDF-HFP) electrolyte. This work offers an in-depth insight into the understanding of the energy storage mechanism of N-rich carbon electrodes in different electrolyte media.

Convenient and Controllable Synthesis of Poly(2-oxazoline)-Conjugated Doxorubicin for Regulating Anti-Tumor Selectivity.

Polyethylene glycol (PEG)-doxorubicin (DOX) conjugation is an important strategy to improve toxicity and enhance clinically therapeutic efficacy. However, with the frequent use of PEG-modified drugs, the accumulation of anti-PEG antibodies has become a tough issue, which limits the application of PEG-drug conjugation. As an alternative solution, poly(2-oxazoline) (POX)-DOX conjugation has shown great potential in the anti-tumor field, but the reported conjugation process of POX with DOX has drawbacks such as complex synthetic steps and purification. Herein, we propose a convenient and controllable strategy for the synthesis of POX-DOX conjugation with different chain lengths and narrow dispersity by N-boc-2-bromoacetohydrazide-initiated 2-ethyl-oxazoline polymerization and the subsequent deprotection of the N-Boc group and direct reaction with DOX. The DOX-PEtOx conjugates were firstly purified, and the successful conjugations were confirmed through various characterization methods. The synthetic DOX-PEtOxn conjugates reduce the toxicity of DOX and increase the selectivity to tumor cells, reflecting the promising application of this POX-DOX conjugation strategy in drug modification and development.

Excess Deaths of Gastrointestinal, Liver, and Pancreatic Diseases During the COVID-19 Pandemic in the United States.

Objectives: To evaluate excess deaths of gastrointestinal, liver, and pancreatic diseases in the United States during the COVID-19 pandemic. Methods: We retrieved weekly death counts from National Vital Statistics System and fitted them with a quasi-Poisson regression model. Cause-specific excess deaths were calculated by the difference between observed and expected deaths with adjustment for temporal trend and seasonality. Demographic disparities and temporal-spatial patterns were evaluated for different diseases. Results: From March 2020 to September 2022, the increased mortality (measured by excess risks) for Clostridium difficile colitis, gastrointestinal hemorrhage, and acute pancreatitis were 35.9%; 24.8%; and 20.6% higher than the expected. For alcoholic liver disease, fibrosis/cirrhosis, and hepatic failure, the excess risks were 1.4-2.8 times higher among younger inhabitants than older inhabitants. The excess deaths of selected diseases were persistently observed across multiple epidemic waves with fluctuating trends for gastrointestinal hemorrhage and fibrosis/cirrhosis and an increasing trend for C. difficile colitis. Conclusion: The persistently observed excess deaths of digestive diseases highlights the importance for healthcare authorities to develop sustainable strategies in response to the long-term circulating of SARS-CoV-2 in the community.

Switching from membrane disrupting to membrane crossing, an effective strategy in designing antibacterial polypeptide.

Drug-resistant bacterial infections have caused serious threats to human health and call for effective antibacterial agents that have low propensity to induce antimicrobial resistance. Host defense peptide-mimicking peptides are actively explored, among which poly-ß-l-lysine displays potent antibacterial activity but high cytotoxicity due to the helical structure and strong membrane disruption effect. Here, we report an effective strategy to optimize antimicrobial peptides by switching membrane disrupting to membrane penetrating and intracellular targeting by breaking the helical structure using racemic residues. Introducing ß-homo-glycine into poly-ß-lysine effectively reduces the toxicity of resulting poly-ß-peptides and affords the optimal poly-ß-peptide, ßLys50HG50, which shows potent antibacterial activity against clinically isolated methicillin-resistant Staphylococcus aureus (MRSA) and MRSA persister cells, excellent biosafety, no antimicrobial resistance, and strong therapeutic potential in both local and systemic MRSA infections. The optimal poly-ß-peptide demonstrates strong therapeutic potential and implies the success of our approach as a generalizable strategy in designing promising antibacterial polypeptides.

Refined Contact Map Prediction of Peptides Based on GCN and ResNet.

Predicting peptide inter-residue contact maps plays an important role in computational biology, which determines the topology of the peptide structure. However, due to the limited number of known homologous structures, there is still much room for inter-residue contact map prediction. Current models are not sufficient for capturing the high accuracy relationship between the residues, especially for those with a long-range distance. In this article, we developed a novel deep neural network framework to refine the rough contact map produced by the existing methods. The rough contact map is used to construct the residue graph that is processed by the graph convolutional neural network (GCN). GCN can better capture the global information and is therefore used to grasp the long-range contact relationship. The residual convolutional neural network is also applied in the framework for learning local information. We conducted the experiments on four different test datasets, and the inter-residue long-range contact map prediction accuracy demonstrates the effectiveness of our proposed method.