Cryo-EM structure of HQNO-bound alternative complex III from the anoxygenic phototrophic bacterium Chloroflexus aurantiacus.

Alternative complex III (ACIII) couples quinol oxidation and electron acceptor reduction with potential transmembrane proton translocation. It is compositionally and structurally different from the cytochrome bc1/b6f complexes but functionally replaces these enzymes in the photosynthetic and/or respiratory electron transport chains (ETCs) of many bacteria. However, the true compositions and architectures of ACIIIs remain unclear, as do their structural and functional relevance in mediating the ETCs. We here determined cryogenic electron microscopy structures of photosynthetic ACIII isolated from Chloroflexus aurantiacus (CaACIIIp), in apo-form and in complexed form bound to a menadiol analog 2-heptyl-4-hydroxyquinoline-N-oxide. Besides 6 canonical subunits (ActABCDEF), the structures revealed conformations of 2 previously unresolved subunits, ActG and I, which contributed to the complex stability. We also elucidated the structural basis of menaquinol oxidation and subsequent electron transfer along the [3Fe-4S]-6 hemes wire to its periplasmic electron acceptors, using electron paramagnetic resonance, spectroelectrochemistry, enzymatic analyses, and molecular dynamics simulations. A unique insertion loop in ActE was shown to function in determining the binding specificity of CaACIIIp for downstream electron acceptors. This study broadens our understanding of the structural diversity and molecular evolution of ACIIIs, enabling further investigation of the (mena)quinol oxidoreductases-evolved coupling mechanism in bacterial energy conservation.

Sirt6 ablation in the liver causes fatty liver that increases cancer risky by upregulating Serpina12.

Non-alcoholic fatty liver disease is a chronic liver abnormality that exhibits high variability and can lead to liver cancer in advanced stages. Hepatic ablation of SIRT6 results in fatty liver disease, yet the potential mechanism of SIRT6 deficiency, particularly in relation to downstream mediators for NAFLD, remains elusive. Here we identify Serpina12 as a key gene regulated by Sirt6 that plays a crucial function in energy homeostasis. Specifically, Sirt6 suppresses Serpina12 expression through histone deacetylation at its promoter region, after which the transcription factor, Cebpα, binds to and regulates its expression. Sirt6 deficiency results in an increased expression of Serpina12 in hepatocytes, which enhances insulin signaling and promotes lipid accumulation. Importantly, CRISPR-Cas9 mediated Serpina12 knockout in the liver ameliorated fatty liver disease caused by Sirt6 ablation. Finally, we demonstrate that Sirt6 functions as a tumor suppressor in the liver, and consequently, deletion of Sirt6 in the liver leads to not only the spontaneous development of tumors but also enhanced tumorigenesis in response to DEN treatment or under conditions of obesity.

53BP1 inhibits homologous recombination in Brca1-deficient cells by blocking resection of DNA breaks.

Defective DNA repair by homologous recombination (HR) is thought to be a major contributor to tumorigenesis in individuals carrying Brca1 mutations. Here, we show that DNA breaks in Brca1-deficient cells are aberrantly joined into complex chromosome rearrangements by a process dependent on the nonhomologous end-joining (NHEJ) factors 53BP1 and DNA ligase 4. Loss of 53BP1 alleviates hypersensitivity of Brca1 mutant cells to PARP inhibition and restores error-free repair by HR. Mechanistically, 53BP1 deletion promotes ATM-dependent processing of broken DNA ends to produce recombinogenic single-stranded DNA competent for HR. In contrast, Lig4 deficiency does not rescue the HR defect in Brca1 mutant cells but prevents the joining of chromatid breaks into chromosome rearrangements. Our results illustrate that HR and NHEJ compete to process DNA breaks that arise during DNA replication and that shifting the balance between these pathways can be exploited to selectively protect or kill cells harboring Brca1 mutations.

A narrative review on advances in neoadjuvant immunotherapy for esophageal cancer: Molecular biomarkers and future directions.

Esophageal cancer has a poor prognosis and survival rate due to its high incidence in Asia, lack of early symptoms and limited treatment options. In recent years, many clinical trials have demonstrated that immunotherapy has greatly improved the survival of patients with esophageal cancer. In addition, the combination of neoadjuvant immunotherapy with other popular therapeutic regimens has shown good efficacy and safety. In this review, we summarize the progress of clinical trials and some breakthroughs in neoadjuvant immunotherapy for esophageal cancer in recent years and suggest the possibility of multimodal neoadjuvant immunotherapy regimens, as well as directions for future development.

Preparation and brain targeting effects study of recombinant human ferritin nanoparticles.

Human heavy-chain ferritin is a naturally occurring protein with high stability and multifunctionality in biological systems. This study aims to utilize a prokaryotic expression system to produce recombinant human heavy-chain ferritin nanoparticles and investigate their targeting ability in brain tissue. The human heavy-chain ferritin gene was cloned into the prokaryotic expression vector pET28a and transformed into Escherichia coli BL21 (DE3) competent cells to explore optimal expression conditions. The recombinant protein was then purified to evaluate its immunoreactivity and characteristics. Additionally, the distribution of the administered protein in normal mice and its permeability in an in vitro blood-brain barrier (BBB) model were measured. The results demonstrate that the purified protein can self-assemble extracellularly into nano-cage structures of approximately 10 nm and is recognized by corresponding antibodies. The protein effectively penetrates the blood-brain barrier and exhibits slow clearance in mouse brain tissue, showing excellent permeability in the in vitro BBB model. This study highlights the stable expression of recombinant human heavy-chain ferritin using the Escherichia coli prokaryotic expression system, characterized by favorable nano-cage structures and biological activity. Its exceptional brain tissue targeting and slow metabolism lay an experimental foundation for its application in neuropharmaceutical delivery and vaccine development fields.

Sialic Acid-Functionalized Pyroptosis Nanotuner for Epigenetic Regulation and Enhanced Cancer Immunotherapy.

The efficacy of immune checkpoint blockade (ICB) in promoting an immune response against tumors still encounters challenges such as low response rates and off-target effects. Pyroptosis, an immunogenic cell death (ICD) mechanism, holds the potential to overcome the limitations of ICB by activating and recruiting immune cells. However, the expression of the pyroptosis-related protein Gasdermin-E(GSDME) in some tumors is limited due to mRNA methylation. To overcome this obstacle, sialic acid-functionalized liposomes coloaded with decitabine, a demethylation drug, and triclabendazole, a pyroptosis-inducing drug are developed. This nanosystem primarily accumulates at tumor sites via sialic acid and the Siglec receptor, elevating liposome accumulation in tumors up to 3.84-fold at 24 h and leading to the upregulation of pyroptosis-related proteins and caspase-3/GSDME-dependent pyroptosis. Consequently, it facilitates the infiltration of CD8+ T cells into the tumor microenvironment and enhances the efficacy of ICB therapy. The tumor inhibition rate of the treatment group is 89.1% at 21 days. This study highlights the potential of sialic acid-functionalized pyroptosis nanotuners as a promising approach for improving the efficacy of ICB therapy in tumors with low GSDME expression through epigenetic alteration and ICD.

Diffusion model based on generalized map for accelerated MRI.

In recent years, diffusion models have made significant progress in accelerating magnetic resonance imaging. Nevertheless, it still has inherent limitations, such as prolonged iteration times and sluggish convergence rates. In this work, we present a novel generalized map generation model based on mean-reverting SDE, called GM-SDE, to alleviate these shortcomings. Notably, the core idea of GM-SDE is optimizing the initial values of the iterative algorithm. Specifically, the training process of GM-SDE diffuses the original k-space data to an intermediary degraded state with fixed Gaussian noise, while the reconstruction process generates the data by reversing this process. Based on the generalized map, three variants of GM-SDE are proposed to learn k-space data with different structural characteristics to improve the effectiveness of model training. GM-SDE also exhibits flexibility, as it can be integrated with traditional constraints, thereby further enhancing its overall performance. Experimental results showed that the proposed method can reduce reconstruction time and deliver excellent image reconstruction capabilities compared to the complete diffusion-based method.

Protein Kinase C Modulation Determines the Mesoderm/Extraembryonic Fate Under BMP4 Induction From Human Pluripotent Stem Cells.

The interplay among mitogenic signaling pathways is crucial for proper embryogenesis. These pathways collaboratively act through intracellular master regulators to determine specific cell fates. Identifying the master regulators is critical to understanding embryogenesis and to developing new applications of pluripotent stem cells. In this report, we demonstrate protein kinase C (PKC) as an intrinsic master switch between embryonic and extraembryonic cell fates in the differentiation of human pluripotent stem cells (hPSCs). PKCs are essential to induce the extraembryonic lineage downstream of BMP4 and other mitogenic modulators. PKC-alpha (PKCα) suppresses BMP4-induced mesoderm differentiation, and PKC-delta (PKCδ) is required for trophoblast cell fate. PKC activation overrides mesoderm induction conditions and leads to extraembryonic fate. In contrast, PKC inhibition leads to ß-catenin (CTNNB1) activation, switching cell fate from trophoblast to mesoderm lineages. This study establishes PKC as a signaling boundary directing the segregation of extraembryonic and embryonic lineages. The manipulation of intrinsic PKC activity could greatly enhance cell differentiation under mitogenic regulation in stem cell applications.

UFMylation of HRD1 regulates endoplasmic reticulum homeostasis.

Ubiquitin fold modifier 1 is a small ubiquitin-like protein modifier that is essential for embryonic development of metazoans. Although UFMylation has been connected to endoplasmic reticulum homeostasis, the underlying mechanisms and the relevant cellular targets are largely unknown. Here, we show that HRD1, a ubiquitin ligase of ER-associated protein degradation (ERAD), is a novel substrate of UFM1 conjugation. HRD1 interacts with UFMylation components UFL1 and DDRGK1 and is UFMylated at Lys610 residue. In UFL1-depleted cells, the stability of HRD1 is increased and its ubiquitination modification is reduced. In the event of ER stress, the UFMylation and ubiquitination modification of HRD1 is gradually inhibited over time. Alteration of HRD1 Lys610 residue to arginine impairs its ability to degrade unfolded or misfolded proteins to disturb protein processing in ER. These results suggest that UFMylation of HRD1 facilitates ERAD function to maintain ER homeostasis.

Characterization of individual spores of two biological insecticides, Bacillus thuringiensis and Lysinibacillus sphaericus, in response to glutaraldehyde using single-cell optical approaches.

Bacillus thuringiensis (Bt) and Lysinibacillus sphaericus (Ls) are the most widely used microbial insecticides. Both encounter unfavorable environmental factors and pesticides in the field. Here, the responses of Bt and Ls spores to glutaraldehyde were characterized using Raman spectroscopy and differential interference contrast imaging at the single-cell level. Bt spores were more sensitive to glutaraldehyde than Ls spores under prolonged exposure: <1.0% of Bt spores were viable after 10 min of 0.5% (v/v) glutaraldehyde treatment, compared to ~ 20% of Ls spores. The Raman spectra of glutaraldehyde-treated Bt and Ls spores were almost identical to those of untreated spores; however, the germination process of individual spores was significantly altered. The time to onset of germination, the period of rapid Ca2+-2,6-pyridinedicarboxylic acid (CaDPA) release, and the period of cortex hydrolysis of treated Bt spores were significantly longer than those of untreated spores, with dodecylamine germination being particularly affected. Similarly, the germination of treated Ls spores was significantly prolonged, although the prolongation was less than that of Bt spores. Although the interiors of Bt and Ls spores were undamaged and CaDPA did not leak, proteins and structures involved in spore germination could be severely damaged, resulting in slower and significantly prolonged germination. This study provides insights into the impact of glutaraldehyde on bacterial spores at the single cell level and the variability in spore response to glutaraldehyde across species and populations.

MolProphet: A One-Stop, General Purpose, and AI-Based Platform for the Early Stages of Drug Discovery.

Artificial intelligence (AI) is an effective tool to accelerate drug discovery and cut costs in discovery processes. Many successful AI applications are reported in the early stages of small molecule drug discovery. However, most of those applications require a deep understanding of software and hardware, and focus on a single field that implies data normalization and transfer between those applications is still a challenge for normal users. It usually limits the application of AI in drug discovery. Here, based on a series of robust models, we formed a one-stop, general purpose, and AI-based drug discovery platform, MolProphet, to provide complete functionalities in the early stages of small molecule drug discovery, including AI-based target pocket prediction, hit discovery and lead optimization, and compound targeting, as well as abundant analyzing tools to check the results. MolProphet is an accessible and user-friendly web-based platform that is fully designed according to the practices in the drug discovery industry. The molecule screened, generated, or optimized by the MolProphet is purchasable and synthesizable at low cost but with good drug-likeness. More than 400 users from industry and academia have used MolProphet in their work. We hope this platform can provide a powerful solution to assist each normal researcher in drug design and related research areas. It is available for everyone at https://www.molprophet.com/.

Identification of Hub Genes in Liver Hepatocellular Carcinoma Based on Weighted Gene Co-expression Network Analysis.

Liver hepatocellular carcinoma (LIHC) is a malignant cancer with high incidence and poor prognosis. To investigate the correlation between hub genes and progression of LIHC and to provided potential prognostic markers and therapy targets for LIHC. Our study mainly used The Cancer Genome Atlas (TCGA) LIHC database and the gene expression profiles of GSE54236 from the Gene Expression Omnibus (GEO) to explore the differential co-expression genes between LIHC and normal tissues. The differential co-expression genes were extracted by Weighted Gene Co-expression Network Analysis (WGCNA) and differential gene expression analysis methods. The Genetic Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were carried out to annotate the function of differential genes. Then the hub genes were validated using protein-protein interaction (PPI) network. And the expression level and prognostic analysis were performed. The probable associations between the expression of hub genes and both tumor purity and infiltration of immune cells were explored by TIMER. A total of 68 differential co-expression genes were extracted. These genes were mainly enriched in complement activation (biological process), collagen trimer (cellular component), carbohydrate binding and receptor ligand activity (molecular function) and cytokine - cytokine receptor interaction. Then we demonstrated that the 10 hub genes (CFP, CLEC1B, CLEC4G, CLEC4M, FCN2, FCN3, PAMR1 and TIMD4) were weakly expressed in LIHC tissues, the qRT-PCR results of clinical samples showed that six genes were significantly downregulated in LIHC patients compared with adjacent tissues. Worse overall survival (OS) and disease-free survival (DFS) in LIHC patients were associated with the lower expression of CFP, CLEC1B, FCN3 and TIMD4. Ten hub genes had positive association with tumor purity. CFP, CLEC1B, FCN3 and TIMD4 could serve as novel potential molecular targets for prognosis prediction in LIHC.

Research Progress on Detection of Pathogens in Medical Wastewater by Electrochemical Biosensors.

The detection of pathogens in medical wastewater is crucial due to the high content of pathogenic microorganisms that pose significant risks to public health and the environment. Medical wastewater, which includes waste from infectious disease and tuberculosis facilities, as well as comprehensive medical institutions, contains a variety of pathogens such as bacteria, viruses, fungi, and parasites. Traditional detection methods like nucleic acid detection and immunological assays, while effective, are often time-consuming, expensive, and not suitable for rapid detection in underdeveloped areas. Electrochemical biosensors offer a promising alternative with advantages including simplicity, rapid response, portability, and low cost. This paper reviews the sources of pathogens in medical wastewater, highlighting specific bacteria (e.g., E. coli, Salmonella, Staphylococcus aureus), viruses (e.g., enterovirus, respiratory viruses, hepatitis virus), parasites, and fungi. It also discusses various electrochemical biosensing techniques such as voltammetry, conductometry, impedance, photoelectrochemical, and electrochemiluminescent biosensors. These technologies facilitate the rapid, sensitive, and specific detection of pathogens, thereby supporting public health and environmental safety. Future research may should pay more attention on enhancing sensor sensitivity and specificity, developing portable and cost-effective devices, and innovating detection methods for diverse pathogens to improve public health protection and environmental monitoring.

Cardioprotective and anti-inflammatory effects of Caveolin 1 in experimental diabetic cardiomyopathy.

Previous studies of the Caveolin 1 (Cav1) protein and caveolae, which are lipid raft structures found on the plasma membranes of certain cells, are associated with fat metabolism disorders, inflammation, diabetes, and cardiovascular disease. However, there have been no reports linking Cav1 to diabetic cardiomyopathy (DCM). In the present study, we established a relationship between Cav1 and the development of DCM. We found that compared with Cav1+/+ mice, Cav1-/- diabetic mice exhibited more severe cardiac injury, increased activation of NF-κB signaling, and up-regulation of downstream genes, including hypertrophic factors and inflammatory fibrosis factors in heart tissues. Additionally, in vitro results showed that knocking down Cav1 further activated HG-induced NF-κB signaling, increased the expression of downstream target genes, and decreased the expression of inhibitor α of NF-κB (iκBα), all of which have been linked to DCM pathogenesis. In contrast, Cav1 overexpression resulted in the opposite effects. Our study suggests that Cav1 knockdown promotes cardiac injury in DCM by activating the NF-κB signaling pathway, and targeting Cav1 may lead to the development of novel treatments for DCM.

Depression and anxiety among hemophilia patients enrolled in clinical trials: a multi-center cohort study.

Hemophilia patients enrolled in clinical trials often exhibit various physical and psychological symptoms. However, little is known about anxiety and depression among them. This study assessed the effects of depression and anxiety on hemophilia patients enrolled in clinical trials and identified risk factors for these disorders. A multi-center, cohort study was conducted from January to December 2022. Sixty-nine hemophilia patients who enrolled in clinical trials participated at baseline (T1, prior to treatment initiation) and completed the informed consent. Risk factors were measured at baseline to predict depression and anxiety at 3 months (T2). Sixty-four hemophilia patients were included in the final analysis. More hemophilia patients had moderate-severe depression (28 [43.75%]) and anxiety (16 [25.00%]) at T2 than at T1 (12 [18.75]), (5 [7.81%]). Depression was aggravated in 23 (35.94%) patients and anxiety was aggravated in 12 (18.75%) patients. Frequently acquired medical information (OR 11.378, CI 1.319-98.114, P = 0.027), baseline GAD-7 (OR 1.341, CI 1.015-1.772, P = 0. 039) and PHQ-9 (OR 1.465, CI 1.039-2.065, P = 0.029) are important factors predicting depression and anxiety in hemophilia patients. Hemophilia patients enrolled in a clinical trial have significant anxiety and depression. The frequency of acquiring medical information and the baseline PHQ-9 and GAD-7 scores were risk factors for anxiety and depression. Thus, hemophilia patients should receive education regarding clinical trials and undergo evaluations of their anxiety and depression; these changes will enable prompt detection of their psychological burden and identify potential psychological intervention strategies.

Applications of lung cancer organoids in precision medicine: from bench to bedside.

As the leading cause of cancer-related mortality, lung cancer continues to pose a menacing threat to human health worldwide. Lung cancer treatment options primarily rely on chemoradiotherapy, surgery, targeted therapy, or immunotherapy. Despite significant progress in research and treatment, the 5-year survival rate for lung cancer patients is only 10-20%. There is an urgent need to develop more reliable preclinical models and valid therapeutic approaches. Patient-derived organoids with highly reduced tumour heterogeneity have emerged as a promising model for high-throughput drug screening to guide treatment of lung cancer patients. Organoid technology offers a novel platform for disease modelling, biobanking and drug development. The expected benefit of organoids is for cancer patients as the subsequent precision medicine technology. Over the past few years, numerous basic and clinical studies have been conducted on lung cancer organoids, highlighting the significant contributions of this technique. This review comprehensively examines the current state-of-the-art technologies and applications relevant to the formation of lung cancer organoids, as well as the potential of organoids in precision medicine and drug testing. Video Abstract.

Composite Hydrogel for the Targeted Capture and Photothermal Killing of Bacteria toward Facilitating Wound Healing.

Pathogenic infections pose a significant risk to public health and are regarded as one of the most difficult clinical treatment obstacles. A reliable and safe photothermal antibacterial platform is a promising technique for the treatment of bacterial infections. Given the damage that high temperatures cause in normal tissues and cells, a multifunctional hydrogel driven by photothermal energy is created by trapping bacteria to reduce heat transfer loss and conduct low-temperature photothermal sterilization efficiently. The 3-aminobenzene boronic acid (ABA)-modified graphene oxide is combined with carboxymethyl chitosan (CMCS) and cellulose nanocrystalline (CNC) networks to create the ABA-GO/CNC/CMCS composite hydrogel (composite gel). The obtained composite gel displays a uniform three-dimensional network structure, which can be rapidly heated to 48 °C under infrared light irradiation and is beneficial for killing wound infection bacteria and promoting wound healing. The results of animal experiments show that the composite gel significantly reduces inflammation by killing >99.99% of bacteria under near-infrared light irradiation. The result also demonstrates that it increases the granulation tissue thickness and collagen distribution and promotes wound healing. After treatment for 14 days, compared with the remaining 27.73% of the remaining wound area in the control group, the wound area in the composite gel with NIR group is only 0.91%. It significantly accelerates the wound healing process of Staphylococcus aureus infection and shows great potential for clinical application.

Machine learning model for anti-cancer drug combinations: Analysis, prediction, and validation.

Drug combination therapy is a highly effective approach for enhancing the therapeutic efficacy of anti-cancer drugs and overcoming drug resistance. However, the innumerable possible drug combinations make it impractical to screen all synergistic drug pairs. Moreover, biological insights into synergistic drug pairs are still lacking. To address this challenge, we systematically analyzed drug combination datasets curated from multiple databases to identify drug pairs more likely to show synergy. We classified drug pairs based on their MoA and discovered that 110 MoA pairs were significantly enriched in synergy in at least one type of cancer. To improve the accuracy of predicting synergistic effects of drug pairs, we developed a suite of machine learning models that achieve better predictive performance. Unlike most previous methods that were rarely validated by wet-lab experiments, our models were validated using two-dimensional cell lines and three-dimensional tumor slice culture (3D-TSC) models, implying their practical utility. Our prediction and validation results indicated that the combination of the RTK inhibitors Lapatinib and Pazopanib exhibited a strong therapeutic effect in breast cancer by blocking the downstream PI3K/AKT/mTOR signaling pathway. Furthermore, we incorporated molecular features to identify potential biomarkers for synergistic drug pairs, and almost all potential biomarkers found connections between drug targets and corresponding molecular features using protein-protein interaction network. Overall, this study provides valuable insights to complement and guide rational efforts to develop drug combination treatments.

The subacute toxicity and underlying mechanisms of biomimetic mesoporous polydopamine nanoparticles.

Recently, mesoporous nanomaterials with widespread applications have attracted great interest in the field of drug delivery due to their unique structure and good physiochemical properties. As a biomimetic nanomaterial, mesoporous polydopamine (MPDA) possesses both a superior nature and good compatibility, endowing it with good clinical transformation prospects compared with other inorganic mesoporous nanocarriers. However, the subacute toxicity and underlying mechanisms of biomimetic mesoporous polydopamine nanoparticles remain uncertain. Herein, we prepared MPDAs by a soft template method and evaluated their primary physiochemical properties and metabolite toxicity, as well as potential mechanisms. The results demonstrated that MPDA injection at low (3.61 mg/kg) and medium doses (10.87 mg/kg) did not significantly change the body weight, organ index or routine blood parameters. In contrast, high-dose MPDA injection (78.57 mg/kg) is associated with disturbances in the gut microbiota, activation of inflammatory pathways through the abnormal metabolism of bile acids and unsaturated fatty acids, and potential oxidative stress injury. In sum, the MPDA dose applied should be controlled during the treatment. This study first provides a systematic evaluation of metabolite toxicity and related mechanisms for MPDA-based nanoparticles, filling the gap between their research and clinical transformation as a drug delivery nanoplatform.

Nano drug delivery systems: a promising approach to scar prevention and treatment.

Scar formation is a common physiological process that occurs after injury, but in some cases, pathological scars can develop, leading to serious physiological and psychological effects. Unfortunately, there are currently no effective means to intervene in scar formation, and the structural features of scars and their unclear mechanisms make prevention and treatment even more challenging. However, the emergence of nanotechnology in drug delivery systems offers a promising avenue for the prevention and treatment of scars. Nanomaterials possess unique properties that make them well suited for addressing issues related to transdermal drug delivery, drug solubility, and controlled release. Herein, we summarize the recent progress made in the use of nanotechnology for the prevention and treatment of scars. We examine the mechanisms involved and the advantages offered by various types of nanomaterials. We also highlight the outstanding challenges and questions that need to be addressed to maximize the potential of nanotechnology in scar intervention. Overall, with further development, nanotechnology could significantly improve the prevention and treatment of pathological scars, providing a brighter outlook for those affected by this condition.