Effect of platelet-rich plasma combined with negative pressure wound therapy in treating patients with chronic wounds: A meta-analysis.

A meta-analysis was conducted to comprehensively explore the effects of platelet-rich plasma (PRP) combined with negative pressure wound therapy (NPWT) in treating patients with chronic wounds. Computer searches were conducted, from database infection to November 2023, in EMBASE, Google Scholar, Cochrane Library, PubMed, Wanfang and China National Knowledge Infrastructure databases for randomized controlled trials (RCTs) on the use of PRP combined with NPWT technology for treating chronic wounds. Two researchers independently screened the literature, extracted data and conducted quality assessments according to the inclusion and exclusion criteria. Stata 17.0 software was employed for data analysis. Overall, 18 RCTs involving 1294 patients with chronic wounds were included. The analysis revealed that, compared with NPWT alone, the use of PRP combined with NPWT technology significantly improved the healing rate (odds ratios [OR] = 1.92, 95% confidence intervals [CIs]: 1.43-2.58, p < 0.001) and total effective rate (OR = 1.31, 95% CI: 1.23-1.39, p < 0.001), and also significantly shortened the healing time of the wound (standardized mean difference = -2.01, 95% CI: -2.58 to -1.45, p < 0.001). This study indicates that the treatment of chronic wounds with PRP combined with NPWT technology can significantly enhance clinical repair effectiveness and accelerate wound healing, with a high healing rate, and is worth further promotion and practice.

Diagnosis knowledge constrained network based on first-order logic for syndrome differentiation.

Traditional Chinese medicine (TCM) has been recognized worldwide as a valuable asset of human medicine. The procedure of TCM is to treatment based on syndrome differentiation. However, the effect of TCM syndrome differentiation relies heavily on the experience of doctors. The gratifying progress of machine learning research in recent years has brought new ideas for TCM syndrome differentiation. In this paper, we propose a deep network model for TCM syndrome differentiation, which improves network performance by injecting TCM syndrome differentiation knowledge in the form of first-order logic into the deep network. Experimental results show that the accuracy of our proposed model reaches 89%, which is significantly better than the deep learning model MLP and other traditional machine learning models. In addition, we present the collected and formatted TCM syndrome differentiation (TSD) dataset, which contains more than 40,000 TCM clinical records. Moreover, 45 symptoms (""), 322 patterns(""), and more than 500 symptoms are labeled in TSD respectively. To the best of our knowledge, this is the first TCM syndrome differentiation dataset labeling diseases, syndromes and pattern. Such detailed labeling is helpful to explore the relationship between various elements of syndrome differentiation.

Elemene Antitumor Drugs Development Based on "Molecular Compatibility Theory" and Clinical Application: A Retrospective and Prospective Outlook.

Elemene, derived from Curcuma wenyujin, one of the "8 famous genuine medicinal materials of Zhejiang province," exhibits remarkable antitumor activity. It has gained wide recognition in clinical practice for effectiveness on tumors. Dr. XIE Tian, introduced the innovative concept of "molecular compatibility theory" by combining Chinese medicine principles, specifically the "monarch, minister, assistant, and envoy" theory, with modern biomedical technology. This groundbreaking approach, along with a systematic analysis of Chinese medicine and modern biomedical knowledge, led to the development of elemene nanoliposome formulations. These novel formulations offer numerous advantages, including low toxicity, well-defined composition, synergistic effects on multiple targets, and excellent biocompatibility. Following the principles of the "molecular compatibility theory", further exploration of cancer treatment strategies and methods based on elemene was undertaken. This comprehensive review consolidates the current understanding of elemene's potential antitumor mechanisms, recent clinical investigations, advancements in drug delivery systems, and structural modifications. The ultimate goal of this review is to establish a solid theoretical foundation for researchers, empowering them to develop more effective antitumor drugs based on the principles of "molecular compatibility theory".

Discovery of plant-derived anti-tumor natural products: Potential leads for anti-tumor drug discovery.

Natural products represent a paramount source of novel drugs. Numerous plant-derived natural products have demonstrated potent anti-tumor properties, thereby garnering considerable interest in their potential as anti-tumor drugs. This review compiles an overview of 242 recently discovered natural products, spanning the period from 2018 to the present. These natural products, which include 69 terpenoids, 42 alkaloids, 39 flavonoids, 21 steroids, 14 phenylpropanoids, 5 quinolines and 52 other compounds, are characterized by their respective chemical structures, anti-tumor activities, and mechanisms of action. By providing an essential reference and fresh insights, this review aims to support and inspire researchers engaged in the fields of natural products and anti-tumor drug discovery.

Click chemistry-aided drug discovery: A retrospective and prospective outlook.

Click chemistry has emerged as a valuable tool for rapid compound synthesis, presenting notable advantages and convenience in the exploration of potential drug candidates. In particular, in situ click chemistry capitalizes on enzymes as reaction templates, leveraging their favorable conformation to selectively link individual building blocks and generate novel hits. This review comprehensively outlines and introduces the extensive use of click chemistry in compound library construction, and hit and lead discovery, supported by specific research examples. Additionally, it discusses the limitations and precautions associated with the application of click chemistry in drug discovery. Our intention for this review is to contribute to the development of a modular synthetic approach for the rapid identification of drug candidates.

Discovery and bioassay of disubstituted ß-elemene-NO donor conjugates: synergistic enhancement in the treatment of leukemia.

Natural products are essential sources of antitumor drugs. One such molecule, ß-elemene, is a potent antitumor compound extracted from Curcuma wenyujin. In the present investigation, a series of novel 13,14-disubstituted nitric oxide (NO)-donor ß-elemene derivatives were designed, with ß-elemene as the foundational compound, and subsequently synthesized to evaluate their therapeutic potential against leukemia. Notably, the derivative labeled as compound 13d demonstrated a potent anti-proliferative activity against the K562 cell line, with a high NO release. In vivo studies indicated that compound 13d could effectively inhibit tumor growth, exhibiting no discernible toxic manifestations. Specifically, a significant tumor growth inhibition rate of 62.9% was observed in the K562 xenograft tumor mouse model. The accumulated data propound the potential therapeutic application of compound 13d in the management of leukemia.

Improving the Physicochemical Stability of Soy Phospholipid-Stabilized Emulsions Loaded with Lutein by the Addition of Sphingomyelin and Cholesterol: Inspired by a Milk Fat Globule Membrane.

The emulsifying performance of glycerophospholipids alone is inferior to proteins, etc., while the sphingomyelin (SM) and cholesterol (Chol) naturally existing in biological membranes could interact with glycerophospholipids to influence the polar lipid arrangement. Inspired by the natural membranes, the effect of SM and Chol on the physicochemical stability of soy phospholipid (SPL)-stabilized emulsions during storage or under environmental stresses was determined. The results indicated that the addition of SM and/or Chol could improve the storage stability of the emulsions and protective effect on lutein significantly (p < 0.05). Except for UV irradiation, the addition of Chol significantly improved the stability of the emulsions against acid, salt, and heat. The strong intermolecular hydrogen bonds and condensed assembly formed by SM and Chol contributed to the best stability of SPL + SM + Chol-stabilized emulsions. The results gave insight into improving the emulsifying properties of glycerophospholipids with SM and Chol.

Clinical features and risk factors analysis for poor outcomes of severe community-acquired pneumonia in children: a nomogram prediction model.

Background: Pneumonia remains the leading cause of death among children aged 1-59 months. The early prediction of poor outcomes (PO) is of critical concern. This study aimed to explore the risk factors relating to PO in severe community-acquired pneumonia (SCAP) and build a PO-predictive nomogram model for children with SCAP. Methods: We retrospectively identified 300 Chinese pediatric patients diagnosed with SCAP who were hospitalized in the Affiliated Hospital of Southwest Medical University from August 1, 2018, to October 31, 2021. Children were divided into the PO and the non-PO groups. The occurrence of PO was designated as the dependent variable. Univariate and multivariate logistic regression analyses were used to identify the risk factors of PO. A nomogram model was constructed from the multivariate logistic regression analysis and internally validated for model discrimination and calibration. The performance of the nomogram was estimated using the concordance index (C-index). Results: According to the efficacy evaluation criteria, 56 of 300 children demonstrated PO. The multivariate logistic regression analysis resulted in the following independent risk factors for PO: co-morbidity (OR: 8.032, 95% CI: 3.556-18.140, P < 0.0001), requiring invasive mechanical ventilation (IMV) (OR: 7.081, 95% CI: 2.250-22.282, P = 0.001), and ALB < 35 g/L (OR: 3.203, 95% CI: 1.151-8.912, P = 0.026). Results of the internal validation confirmed that the model provided good discrimination (concordance index [C-index], 0.876 [95% CI: 0.828-0.925]). The calibration plots in the nomogram model were of high quality. Conclusion: The nomogram facilitated accurate prediction of PO in children diagnosed with SCAP and could be helpful for clinical decision-making.

Building a Flexible and Highly Ionic Conductive Solid Electrolyte Interphase on the Surface of Si@C Anodes by Binary Electrolyte Additives.

Si@C as a high specific capacity anode material for lithium batteries (LIBs) has attracted a lot of attention. However, the severe volume change during lithium de-embedding causes repeated rupture/reconstruction of the solid electrolyte interphase (SEI), resulting in poor cycling stability of the Si-based battery system and thus hindering its application in commercial batteries. Using electrolyte additives to form an excellent SEI is considered to be a cost-effective method to meet this challenge. Here, the classical film-forming additive vinyl carbonate (VC), and the newly emerging lithium salt additive lithium difluorophosphate (LiDFP), are chosen as synergistic additives to improve the electrode-electrolyte interface properties. Final results show that the VC additive generates flexible polycarbonate components at the electrode/electrolyte interface, preventing the fragmentation of Si particles. However, the organic components show high impedance, inhibiting the fast transport of Li+. This defect can be supplemented from the decomposition substances of the LiDFP additive. The derived inorganic products, such as LiF and Li3PO4, can strengthen the reaction kinetics of the electrode, reduce the interfacial impedance, and promote the Li+ transport. Thus, the synergistic effect of VC and LiDFP additives builds an effective SEI with good flexibility and high ionic conductivity and then significantly improves the cycling and rate stability of Si@C anodes. The experimental results show that the utilization of LiDFP and VC additives to modify the Si@C anode interface enhances the capacity retention of the Si@C/Li half-cell after 100 cycles from 68.2% to 85.1%. Besides, the possible mechanism of action between VC and LiDFP is proposed by using the spectral characterization technique and density functional theory (DFT) calculations. This research opens up a new possibility for improvement of SEI, and provides a simple way to achieve high-performance Si-based LIBs.

Development and validation of cancer-associated fibroblasts-related gene landscape in prognosis and immune microenvironment of bladder cancer.

Backgrounds: Bladder cancer (BLCA) is one of the most prevalent cancers of the genitourinary system, the clinical outcomes of patients with BLCA are bad, and the morbidity rate is high. One of the key components of the tumor microenvironment (TME) is cancer-associated fibroblasts (CAFs) which are critically involved in BLCA tumorigenesis. Previous studies have shown the involvement of CAFs in tumor growth, cancer progression, immune evasion, angiogenesis, and chemoresistance in several cancers such as breast, colon, pancreatic, ovarian, and prostate cancers. However, only a few studies have shown the role of CAFs in the occurrence and development of BLCA. Methods: We have retrieved and merged the data on RNA-sequencing of patients with BLCA from databases including "the Cancer Genome Atlas" and "Gene Expression Omnibus." Next, we compared the differences in CAFs-related genes (CRGs) expression between normal and BLCA tissues. Based on CRGs expression, we randomly divided patients into two groups. Next, we determined the correlation between CAFs subtypes and differentially expressed CRGs (DECRGs) between the two subtypes. Furthermore, the "Gene Ontology" and "Kyoto Encyclopedia of Genes and Genomes pathway" enrichment analyses were conducted to determine the functional characteristics between the DECRGs and clinicopathology. Results: We identified five genes (POF1B, ARMCX1, ALDOC, C19orf33, and KRT13) using multivariate COX regression and "Least Absolute Shrinkage and Selection Operator (LASSO) COX regression analysis" for developing a prognostic model and calculating the CRGs-risk score. The TME, mutation, CSC index, and drug sensitivity were also analyzed. Conclusion: We constructed a novel five- CRGs prognostic model, which sheds light on the roles of CAFs in BLCA.

FedADT: An Adaptive Method Based on Derivative Term for Federated Learning.

Federated learning is served as a novel distributed training framework that enables multiple clients of the internet of things to collaboratively train a global model while the data remains local. However, the implement of federated learning faces many problems in practice, such as the large number of training for convergence due to the size of model and the lack of adaptivity by the stochastic gradient-based update at the client side. Meanwhile, it is sensitive to noise during the optimization process that can affect the performance of the final model. For these reasons, we propose Federated Adaptive learning based on Derivative Term, called FedADT in this paper, which incorporates adaptive step size and difference of gradient in the update of local model. To further reduce the influence of noise on the derivative term that is estimated by difference of gradient, we use moving average decay on the derivative term. Moreover, we analyze the convergence performance of the proposed algorithm for non-convex objective function, i.e., the convergence rate of 1/nT can be achieved by choosing appropriate hyper-parameters, where n is the number of clients and T is the number of iterations, respectively. Finally, various experiments for the image classification task are conducted by training widely used convolutional neural network on MNIST and Fashion MNIST datasets to verify the effectiveness of FedADT. In addition, the receiver operating characteristic curve is used to display the result of the proposed algorithm by predicting the categories of clothing on the Fashion MNIST dataset.

YTHDF1 Promotes Bladder Cancer Cell Proliferation via the METTL3/YTHDF1-RPN2-PI3K/AKT/mTOR Axis.

N6-methyladenosine (m6A) is the most common mRNA modification and it plays a critical role in tumor progression, prognoses and therapeutic response. In recent years, more and more studies have shown that m6A modifications play an important role in bladder carcinogenesis and development. However, the regulatory mechanisms of m6A modifications are complex. Whether the m6A reading protein YTHDF1 is involved in the development of bladder cancer remains to be elucidated. The aims of this study were to determine the association between METTL3/YTHDF1 and bladder cancer cell proliferation and cisplatin resistance to explore the downstream target genes of METTL3/YTHDF1 and to explore the therapeutic implications for bladder cancer patients. The results showed that the reduced expression of METTL3/YTHDF1 could lead to decreased bladder cancer cell proliferation and cisplatin sensitivity. Meanwhile, overexpression of the downstream target gene, RPN2, could rescue the effect of reduced METTL3/YTHDF1 expression on bladder cancer cells. In conclusion, this study proposes a novel METTL3/YTHDF1-RPN2-PI3K/AKT/mTOR regulatory axis that affects bladder cancer cell proliferation and cisplatin sensitivity.

Combination of chemotherapy and gaseous signaling molecular therapy: Novel ß-elemene nitric oxide donor derivatives against leukemia.

This study aimed to design and synthesize active hybrids of ß-elemene and nitric oxide (NO) donor pharmacophore as potential agents for treating leukemia. Derivatives reported herein exerted better inhibitory effects against human chronic myeloid leukemia K562 cells compared to ß-elemene (IC50 > 100 µM). The most potent compound 18f showed an IC50 value of 0.53 µM against K562 cells, as well as a high NO release level in vitro. In the K562 xenograft tumor mice model, compound 18f effectively inhibited the growth of the tumor, with a significant inhibition rate of 73.18%. After treatment with compound 18f, the body weight of mice did not decrease, indicating that it possessed good safety profile. All these proved that compound 18f was an excellent potential agent against leukemia.

miR-29a-5p modulates ferroptosis by targeting ferritin heavy chain FTH1 in prostate cancer.

Ferroptosis is a kind of regulatory necrosis caused by phospholipid iron-dependent peroxidation. MiRNAs are known to play key roles in diverse biological functions. However, the molecular basis of miRNA-mediated ferroptosis in prostate cancer has not been fully stated. Here, with TCGA prostate cancer miRNA-seq data, we utilized Multivariate Cox regression analysis to prioritize potential miRNA and validated it in vitro and in vivo. We identified miR-29a-5p by TCGA prostate cancer miRNA-seq dataset. And we confirmed the expression of miR-29a-5p in prostate cancer cell lines. MiR-29a-5p knockdown reduced proliferation in PC-3 and LNCaP cells while increased Fe2+ and malondialdehyde (MDA) levels, the opposite phenomenon was observed with miR-29a-5p overexpression. Luciferase reporter assay showed an interaction between miR-29a-5p and Nrf2 downstream gene FTH1, subsequent rescue experiments also indirectly proved their direct effect. Finally, suppression of miR-29a-5p effectively inhibited tumor growth in vivo. These findings proved that the important role of miR-29a-5p in prostate cancer ferroptosis.

SIRT1 Promotes Cisplatin Resistance in Bladder Cancer via Beclin1 Deacetylation-Mediated Autophagy.

Autophagy-dependent cisplatin resistance poses a challenge in bladder cancer treatment. SIRT1, a protein deacetylase, is involved in autophagy regulation. However, the precise mechanism through which SIRT1 mediates cisplatin resistance in bladder cancer via autophagy remains unclear. In this study, we developed a cisplatin-resistant T24/DDP cell line to investigate this mechanism. The apoptosis rate and cell viability were assessed using flow cytometry and the CCK8 method. The expression levels of the relevant RNA and protein were determined using RT-qPCR and a Western blot analysis, respectively. Immunoprecipitation was utilized to validate the interaction between SIRT1 and Beclin1, as well as to determine the acetylation level of Beclin1. The findings indicated the successful construction of the T24/DDP cell line, which exhibited autophagy-dependent cisplatin resistance. Inhibiting autophagy significantly reduced the drug resistance index of these cells. The T24/DDP cell line showed a high SIRT1 expression level. The overexpression of SIRT1 activated autophagy, thereby further promoting cisplatin resistance in the T24/DDP cell line. Conversely, inhibiting autophagy counteracted the cisplatin-resistance-promoting effects of SIRT1. Silencing SIRT1 led to increased acetylation of Beclin1, the inhibition of autophagy, and a reduction in the cisplatin resistance of the T24/DDP cell line. Introducing a double mutation (lysine 430 and 437 to arginine, 2KR) in Beclin-1 inhibited acetylation and activated autophagy, effectively reversing the decreased cisplatin resistance resulting from SIRT1 silencing. In summary, our study elucidated that SIRT1 promotes cisplatin resistance in human bladder cancer T24 cells through Beclin1-deacetylation-mediated autophagy activation. These findings suggest a potential new strategy for reversing cisplatin resistance in bladder cancer.

Online Learning for DNN Training: A Stochastic Block Adaptive Gradient Algorithm.

Adaptive algorithms are widely used because of their fast convergence rate for training deep neural networks (DNNs). However, the training cost becomes prohibitively expensive due to the computation of the full gradient when training complicated DNN. To reduce the computational cost, we present a stochastic block adaptive gradient online training algorithm in this study, called SBAG. In this algorithm, stochastic block coordinate descent and the adaptive learning rate are utilized at each iteration. We also prove that the regret bound of O T can be achieved via SBAG, in which T is a time horizon. In addition, we use SBAG to train ResNet-34 and DenseNet-121 on CIFAR-10, respectively. The results demonstrate that SBAG has better training speed and generalized ability than other existing training methods.

Pickering Emulsion Stabilized by Tea Seed Cake Protein Nanoparticles as Lutein Carrier.

To effectively deliver lutein, hydrothermally prepared tea seed cake protein nanoparticles (TSCPN) were used to fabricate Pickering emulsion, and the bioaccessibility of lutein encapsulated by Pickering emulsion and the conventional emulsion was evaluated in vitro. The results indicated that the average size and absolute value of zeta potential of TSCPN increased along with the increase in the protein concentration, and 2% protein concentration was adopted to prepare TSCPN. With the increase in the concentration of TSCPN, the size of Pickering emulsion decreased from 337.02 µm to 89.36 µm, and when the TSCPN concentration was greater than 0.6%, all emulsions exhibited good stability during the 14 days storage. Combined with the microstructure result, 1.2% TSCPN was used to stabilize Pickering emulsion. With the increase in ionic concentration (0-400 mM), the particle size of the emulsions increased while the absolute value of zeta potential decreased. TSCPN-based Pickering emulsion was superior to the conventional emulsion for both lutein encapsulation (96.6 ± 1.0% vs. 82.1 ± 1.4%) and bioaccessibility (56.0 ± 1.1% vs. 35.2 ± 1.2%). Thus, TSCPN-based Pickering emulsion in this study have the potential as an effective carrier for lutein.

Whey Protein Isolate Nanofibers Prepared by Subcritical Water Stabilized High Internal Phase Pickering Emulsion to Deliver Curcumin.

This study aimed to design a Pickering emulsion (PE) stabilized by whey protein isolate nanofibers (WPINs) prepared with subcritical water (SW) to encapsulate and prevent curcumin (Cur) degradation. Cur-loaded WPINs-SW stabilized PE (WPINs-SW-PE) and hydrothermally prepared WPINs stabilized PE (WPINs-H-PE) were characterized using the particle size, zeta potential, Congo Red, CD, and TEM. The results indicated that WPINs-SW-PE and WPINs-H-PE showed regular spherical shapes with average lengths of 26.88 ± 1.11 µm and 175.99 ± 2.31 µm, and zeta potential values were -38.00 ± 1.00 mV and -34.60 ± 2.03 mV, respectively. The encapsulation efficiencies of WPINs-SW-PE and WPINs-H-PE for Cur were 96.72 ± 1.05% and 94.07 ± 2.35%. The bio-accessibility of Cur of WPINs-SW-PE and WPINs-H-PE were 57.52 ± 1.24% and 21.94 ± 2.09%. In addition, WPINs-SW-PE had a better loading effect and antioxidant activities compared with WPINs-H-PE. SW could be a potential processing method to prepare a PE, laying the foundation for the subsequent production of functional foods.

Discovery of small-molecule compounds and natural products against Parkinson's disease: Pathological mechanism and structural modification.

Parkinson's disease (PD) is the second common neurodegenerative disease characterized by movement disorder. The symptoms of PD harm both the physical and mental health of patients. However, the current treatment strategies for PD only alleviate the symptoms but cannot recover the degenerative process of dopaminergic neurons. Therefore, it is necessary to develop novel and safe drugs for the treatment of PD. In this review, we comprehensively summarized the detailed pathological mechanisms and potential drugable targets of PD. The approved anti-PD drugs in clinical use and the drug candidates under clinical trials were also listed. More importantly, the compounds in the drug discovery phase with in vivo anti-PD activities in the recent two decades (2000-2020) were summarized. The structure-activity relationships (SARs) were also analyzed. Additionally, we predicted all the reviewed compounds' blood-brain barrier (BBB) permeability and statistically analyzed their pharmacological targets and in vivo anti-PD testing models. It is hoped that this review can provide practical information for researchers in the field of anti-PD drug discovery and promote their research work.

HDAC1/MAO-B dual inhibitors against Alzheimer's disease: Design, synthesis and biological evaluation of N-propargylamine-hydroxamic acid/o-aminobenzamide hybrids.

A series of N-propargylamine-hydroxamic acid/o-aminobenzamide hybrids inhibitors combining the typical pharmacophores of hydroxamic acid/o-aminobenzamide and propargylamine were designed and synthesized as HDAC1/MAO-B dual inhibitors for the treatment of Alzheimer's disease. Most of the hybrids displayed moderate to good MAO-B inhibitory activities. Among them, Hybrid If exhibited the most potent activity against MAO-B and HDAC1 (MAO-B, IC50 = 99.0 nM; HDAC1, IC50 = 21.4 nM) and excellent MAO selectively (MAO-A, IC50 = 9923.0 nM; SI = 100.2). Moreover, compound If significantly reversed Aß1-42-induced PC12 cell damage and decreased the production of intracellular ROS, exhibiting favorable antioxidant activity. More importantly, hybrid If instantly penetrated the BBB and accumulated in brain tissue as well as markedly ameliorated cognitive dysfunction in a Morris water maze ICR mice model. In summary, HDAC1/MAO-B dual inhibitor If is a promising potential agent for the therapy of Alzheimer's disease.