GLGFormer: Global Local Guidance Network for Mucosal Lesion Segmentation in Gastrointestinal Endoscopy Images.

Automatic mucosal lesion segmentation is a critical component in computer-aided clinical support systems for endoscopic image analysis. Image segmentation networks currently rely mainly on convolutional neural networks (CNNs) and Transformers, which have demonstrated strong performance in various applications. However, they cannot cope with blurred lesion boundaries and lesions of different scales in gastrointestinal endoscopy images. To address these challenges, we propose a new Transformer-based network, named GLGFormer, for the task of mucosal lesion segmentation. Specifically, we design the global guidance module to guide single-scale features patch-wise, enabling them to incorporate global information from the global map without information loss. Furthermore, a partial decoder is employed to fuse these enhanced single-scale features, achieving single-scale to multi-scale enhancement. Additionally, the local guidance module is designed to refocus attention on the neighboring patch, thus enhancing local features and refining lesion boundary segmentation. We conduct experiments on a private atrophic gastritis segmentation dataset and four public gastrointestinal polyp segmentation datasets. Compared to the current lesion segmentation networks, our proposed GLGFormer demonstrates outstanding learning and generalization capabilities. On the public dataset ClinicDB, GLGFormer achieved a mean intersection over union (mIoU) of 91.0% and a mean dice coefficient (mDice) of 95.0%. On the private dataset Gastritis-Seg, GLGFormer achieved an mIoU of 90.6% and an mDice of 94.6%.

Thoracic high resolution computed tomography evaluation of imaging abnormalities of 108 lung cancer patients with different pulmonary function.

PURPOSE: Preserved ratio impaired spirometry (PRISm) and chronic obstructive pulmonary disease (COPD) belong to lung function injury. PRISm is a precursor to COPD. We compared and evaluated the different basic information, imaging findings and survival curves of 108 lung cancer patients with different pulmonary function based on high resolution computed tomography (HRCT). METHODS: This retrospective study was performed on 108 lung cancer patients who did pulmonary function test (PFT) and thoracic HRCT. The basic information was evaluated: gender, age, body mass index (BMI), smoke, smoking index (SI). The following pulmonary function findings were evaluated: forced expiratory volume in 1s (FEV1), forced vital capacity (FVC), FEV1/FVC ratio. The following computed tomography (CT) findings were evaluated: appearance (bronchiectasis, pneumonectasis, atelectasis, ground-glass opacities [GGO], interstitial inflammation, thickened bronchial wall), diameter (aortic diameter, pulmonary artery diameter, MPAD/AD ratio, inferior vena cava diameter [IVCD]), tumor (volume, classification, distribution, staging [I, II, III, IV]). Mortality rates were calculated and survival curves were estimated using the Kaplan-Meier method. RESULTS: Compared with normal pulmonary function group, PRISm group and COPD group were predominantly male, older, smoked more, poorer lung function and had shorter survival time after diagnosis. There were more abnormal images in PRISm group and COPD group than in normal lung function group (N-C group). In PRISm group and COPD group, lung cancer was found late, and the tumor volume was larger, mainly central squamous carcinoma. But the opposite was true for the N-C group. The PRISm group and COPD group had significant poor survival probability compared with the normal lung function group. CONCLUSIONS: Considerable differences regarding basic information, pulmonary function, imaging findings and survival curves are found between normal lung function group and lung function injury group. Lung function injury (PRISm and COPD) should be taken into account in future lung cancer screening studies.

Observation of Non-Hermitian Edge Burst Effect in One-Dimensional Photonic Quantum Walk.

Non-Hermitian systems can exhibit unique quantum phases without any Hermitian counterparts. For example, the latest theoretical studies predict a new surprising phenomenon that bulk bands can localize and dissipate prominently at the system boundary, which is dubbed the non-Hermitian edge burst effect. Here we realize a one-dimensional non-Hermitian Su-Schrieffer-Heeger lattice with bulk translation symmetry implemented with a photonic quantum walk. Employing time-resolved single-photon detection to characterize the chiral motion and boundary localization of bulk bands, we determine experimentally that the dynamics underlying the non-Hermitian edge burst effect is due to the interplay of non-Hermitian skin effect and imaginary band gap closing. This new non-Hermitian physical effect deepens our understanding of quantum dynamics in open quantum systems.

On-mask detection of SARS-CoV-2 related substances by surface enhanced Raman scattering.

We have developed a convenient surface-enhanced Raman scattering (SERS) platform based on vertical standing gold nanowires (v-AuNWs) which enabled the on-mask detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) related substances such as the Spike-1 protein and the corresponding pseudo-virus. The Spike-1 protein was clearly distinguished from BSA protein with an accuracy above 99 %, and the detection limit could be achieved down to 0.01 µg/mL. Notably, a similar accuracy was achieved for the pseudo-SARS-CoV-2 (pSARS-2) virus as compared to the pseudo-influenza H7N9 (pH7N9) virus. The sensing strategy and setups could be easily adapted to the real SARS-CoV-2 virus and other highly contagious viruses. It provided a promising way to screen the virus carriers by a fast evaluation of their wearing v-AuNWs integrated face-mask which was mandatory during the pandemic.

Machine Learning-Based Prediction of Helicobacter pylori Infection Study in Adults.

BACKGROUND Helicobacter pylori has a high infection rate worldwide, and epidemiological study of H. pylori is important. Artificial intelligence has been widely used in the field of medical research and has become a hotspot in recent years. This paper proposed a prediction model for H. pylori infection based on machine learning in adults. MATERIAL AND METHODS Adult patients were selected as research participants, and information on 30 factors was collected. The chi-square test, mutual information, ReliefF, and information gain were used to screen the feature factors and establish 2 subsets. We constructed an H. pylori infection prediction model based on XGBoost and optimized the model using a grid search by analyzing the correlation between features. The performance of the model was assessed by comparing its accuracy, recall, precision, F1 score, and AUC with those of 4 other classical machine learning methods. RESULTS The model performed better on the part B subset than on the part A subset. Compared with the other 4 machine learning methods, the model had the highest accuracy, recall, F1 score, and AUC. SHAP was used to evaluate the importance of features in the model. It was found that H. pylori infection of family members, living in rural areas, poor washing hands before meals and after using the toilet were risk factors for H. pylori infection. CONCLUSIONS The model proposed in this paper is superior to other models in predicting H. pylori infection and can provide a scientific basis for identifying the population susceptible to H. pylori and preventing H. pylori infection.

Comparative proteomics reveals that fatty acid metabolism is involved in myocardial adaptation to chronic hypoxic injury.

Congenital heart disease (CHD) is the most serious form of heart disease, and chronic hypoxia is the basic physiological process underlying CHD. Some patients with CHD do not undergo surgery, and thus, they remain susceptible to chronic hypoxia, suggesting that some protective mechanism might exist in CHD patients. However, the mechanism underlying myocardial adaptation to chronic hypoxia remains unclear. Proteomics was used to identify the differentially expressed proteins in cardiomyocytes cultured under hypoxia for different durations. Western blotting assays were used to verify protein expression. A Real-Time Cell Analyzer (RTCA) was used to analyze cell growth. In this study, 3881 proteins were identified by proteomics. Subsequent bioinformatics analysis revealed that proteins were enriched in regulating oxidoreductase activity. Functional similarity cluster analyses showed that chronic hypoxia resulted in proteins enrichment in the mitochondrial metabolic pathway. Further KEGG analyses found that the proteins involved in fatty acid metabolism, the TCA cycle and oxidative phosphorylation were markedly upregulated. Moreover, knockdown of CPT1A or ECI1, which is critical for fatty acid degradation, suppressed the growth of cardiomyocytes under chronic hypoxia. The results of our study revealed that chronic hypoxia activates fatty acid metabolism to maintain the growth of cardiomyocytes.

Genomic and transcriptomic significance of multiple primary lung cancers detected by next-generation sequencing in clinical settings.

Effective diagnosis and understanding of the mechanism of intrapulmonary metastasis (IM) from multiple primary lung cancers (MPLC) aid clinical management. However, the actual detection panels used in the clinic are variable. Current research on tumor microenvironment (TME) of MPLC and IM is insufficient. Therefore, additional investigation into the differential diagnosis and discrepancies in TME between two conditions is crucial. Two hundred and fourteen non-small cell lung cancer patients with multiple tumors were enrolled and 507 samples were subjected to DNA sequencing (NGS 10). Then, DNA and RNA sequencing (master panel) were performed on the specimens from 32 patients, the TME profiles between tumors within each patient and across patients and the differentially expressed genes were compared. Four patients were regrouped with NGS 10 results. Master panel resolved the classifications of six undetermined patients. The TME in MPLC exhibited a high degree of infiltration by natural killer (NK) cells, CD56dim NK cells, endothelial cells, etc., P < 0.05. Conversely, B cells, activated B cells, regulatory cells, immature dendritic cells, etc., P < 0.001, were heavily infiltrated in the IM. NECTIN4 and LILRB4 mRNA were downregulated in the MPLC (P < 0.0001). Additionally, NECTIN4 (P < 0.05) and LILRB4 were linked to improved disease-free survival in the MPLC. In conclusion, IM is screened from MPLC by pathology joint NGS 10 detections, followed by a large NGS panel for indistinguishable patients. A superior prognosis of MPLC may be associated with an immune-activating TME and the downregulation of NECTIN4 and LILRB4 considered as potential drug therapeutic targets.

A Prospective Randomized Controlled Trial Assessing the Impact of Preoperative Combined with Postoperative Progressive Resistance Training on Muscle Strength, Gait, Balance and Function in Patients Undergoing Total Hip Arthroplasty.

Purpose: The aim of this study is to investigate the effects of a preoperative combined with postoperative moderate-intensity progressive resistance training (PRT) of the operative side in patients with hip osteoarthritis (HOA) who are undergoing total hip arthroplasty (THA). The study seeks to evaluate the impact of this combined intervention on muscle strength, gait, balance, and hip joint function in a controlled, measurable, and objective manner. Additionally, the study aims to compare the outcomes of this combined intervention with those of preoperative or postoperative muscle strength training conducted in isolation. Methods: A total of 90 patients with HOA scheduled for unilateral primary THA were randomly assigned to three groups: Pre group (preoperative PRT), Post group (postoperative PRT), and Pre& Post group (preoperative combined with postoperative PRT) focusing on hip flexion, extension, adduction, and abduction of operated side. Muscle strength, gait parameters, balance, and hip function were assessed at specific time points during a 12-month follow-up period. Results: All three groups showed significant improvements in muscle strength, with the Pre& Post group demonstrating the most pronounced and sustained gains. Gait velocity and cadence were significantly improved in the Pre& Post group at 1-month and 3-month postoperative follow-ups compared to the other groups. Similarly, the Pre& Post group exhibited superior balance performance at 3-month and 12-month postoperative follow-ups. The Harris Hip Score also showed better outcomes in the Pre& Post group at all follow-up intervals. Conclusion: Preoperative combined with postoperative moderate-intensity PRT in HOA patients undergoing THA led to superior improvements in muscle strength, gait, balance, and hip joint function compared to preoperative or postoperative PRT alone. This intervention shows significant promise in optimizing postoperative rehabilitation and enhancing patient outcomes following THA.

Enhanced Mechanical Strength and Sustained Drug Release in Carrier-Free Silver-Coordinated Anthraquinone Natural Antibacterial Anti-Inflammatory Hydrogel for Infectious Wound Healing.

The persistent challenge of healing infectious wounds and the rise of bacterial resistance represent significant hurdles in contemporary medicine. In this study, based on the natural small molecule drug Rhein self-assembly to form hydrogels and coordinate assembly with silver ions (Ag+), a sustained-release carrier-free hydrogel with compact structure is constructed to promote the repair of bacterial-infected wounds. As a broad-spectrum antimicrobial agent, Ag+ can avoid the problem of bacterial resistance caused by the abuse of traditional antibiotics. In addition, due to the slow-release properties of Rhein hydrogel, continuous effective concentration of Ag+ at the wound site can be ensured. The assembly of Ag+ and Rhein makes the hydrogel system with enhanced mechanical stability. More importantly, it is found that Rhein effectively promotes skin tissue regeneration and wound healing by reprogramming M1 macrophages into M2 macrophages. Further mechanism studies show that Rhein realizes its powerful anti-inflammatory activity through NRF2/HO-1 activation and NF-κB inhibition. Thus, the hydrogel system combines the excellent antibacterial properties of Ag+ with the excellent anti-inflammatory and tissue regeneration ability of Rhein, providing a new strategy for wound management with dual roles.

Efficient complete denture metal base design via a dental feature-driven segmentation network.

BACKGROUND AND OBJECTIVE: Complete denture is a common restorative treatment in dental patients and the design of the core components (major connector and retentive mesh) of complete denture metal base (CDMB) is the basis of successful restoration. However, the automated design process of CDMB has become a challenging task primarily due to the complexity of manual interaction, low personalization, and low design accuracy. METHODS: To solve the existing problems, we develop a computer-aided Segmentation Network-driven CDMB design framework, called CDMB-SegNet, to automatically generate personalized digital design boundaries for complete dentures of edentulous patients. Specifically, CDMB-SegNet consists of a novel upright-orientation adjustment module (UO-AM), a dental feature-driven segmentation network, and a specific boundary-optimization design module (BO-DM). UO-AM automatically identifies key points for locating spatial attitude of the three-dimensional dental model with arbitrary posture, while BO-DM can result in smoother and more personalized designs for complete denture. In addition, to achieve efficient and accurate feature extraction and segmentation of 3D edentulous models with irregular gingival tissues, the light-weight backbone network is also incorporated into CDMB-SegNet. RESULTS: Experimental results on a large clinical dataset showed that CDMB-SegNet can achieve superior performance over the state-of-the-art methods. Quantitative evaluation (major connector/retentive mesh) showed improved Accuracy (98.54 ± 0.58 %/97.73 ± 0.92 %) and IoU (87.42 ± 5.48 %/70.42 ± 7.95 %), and reduced Maximum Symmetric Surface Distance (4.54 ± 2.06 mm/4.62 ± 1.68 mm), Average Symmetric Surface Distance (1.45 ± 0.63mm/1.28 ± 0.54 mm), Roughness Rate (6.17 ± 1.40 %/6.80 ± 1.23 %) and Vertices Number (23.22 ± 1.85/43.15 ± 2.72). Moreover, CDMB-SegNet shortened the overall design time to around 4 min, which is one tenth of the comparison methods. CONCLUSIONS: CDMB-SegNet is the first intelligent neural network for automatic CDMB design driven by oral big data and dental features. The designed CDMB is able to couple with patient's personalized dental anatomical morphology, providing higher clinical applicability compared with the state-of-the-art methods.

Development and Assessment of a Prediction Model for Alzheimer's Disease Diagnosis Based on Thermoregulation-Related Genes.

BACKGROUND: Alzheimer's disease (AD) is a prevalent neurodegenerative condition among the elderly population and the most common form of dementia, however, we lack potent interventions to arrest its inherent pathogenic vectors. Robust evidence indicates thermoregulatory perturbations during and before the onset of symptoms. Therefore, temperature-regulated biomarkers may offer clues to therapeutic targets during the presymptomatic stage. OBJECTIVE: The purpose of this study is to develop and assess a thermoregulation-related gene prediction model for Alzheimer's Disease diagnosis. METHOD: This study aims to utilize microarray bioinformatic analysis to identify the potential biomarkers of AD by analyzing four microarray datasets (GSE48350, GSE5281, GSE122063, and GSE181279) of AD patients. Furthermore, thermoregulation-associated hub genes were identified, and the expression patterns in the brain were explored. In addition, we explored the infiltration of immune cells with thermoregulation-related hub genes. Diagnostic marker validation was then performed at the single-cell level. Finally, the prediction of targeted drugs was performed based on the hub genes. RESULTS: Through the analysis of four datasets pertaining to AD, a total of five genes associated with temperature regulation were identified. Notably, CCK, CXCR4, SLC27A4, and SLC17A6 emerged as diagnostic markers indicative of AD-related brain injury. Furthermore, in the examination of peripheral blood samples from AD patients, SLC27A4 and CXCR4 were identified as pivotal diagnostic indicators. Regrettably, animal experimentation was not pursued to validate the data; rather, an assessment of temperature regulation-related genes was conducted. Future investigations will be undertaken to establish the correlation between these genes and AD pathology. CONCLUSION: Overall, CCK, CXCR4, SLC27A4, and SLC17A6 can be considered pivotal biomarkers for diagnosing the pathogenesis and molecular functions of AD.

Roles of mir155hg and TNF-α in evaluation of prognosis of patients with systemic lupus erythematosus.

Background: Systemic lupus erythematosus (SLE) is a chronic inflammatory autoimmune disease characterized by multi-organ multi-system inflammation, causing severe damage to various organs or systems. Recent studies have shown that miR-155 can affect the progression of Lupus Nephritis via regulating TNF-a. The present study aims to explore the roles of MIR155HG and TNF-a in the evaluation of prognosis of patients with SLE, so as to provide a basis for clinical work. Methods: A total of 130 patients with SLE admitted to our hospital were selected, were selected from June 2015 to December 2017., and the SLE disease activity index (SLEDAI) score was given. The expressions of MIR155HG and TNF-a were detected via quantitative reverse transcription-polymerase chain reaction (qRT-PCR), the incidence of complications during treatment was observed, and the associations of MIR155HG and TNF-a with SLEDAI before treatment and complications were analyzed. All patients were followed up after discharge, and the related factors to the prognosis of patients were analyzed via Cox regression analysis. Results: The levels of MIR155HG and TNF-a were higher in patients with an SLEDAI score of 10-14 points than those in patients with an SLEDAI score of 5-9 points and 0-4 points. MIR155HG and TNF-a were positively correlated with the incidence of infection, renal damage and cardiac damage (r=0.623, 0.533 and 0.621; r=0.431, 0.498 and 0.552) (P<0.05). Moreover, there was also a positive correlation (r=0.3398, P<0.001) between the expressions of serum MIR155HG and TNF-a in SLE patients. SLEDAI score ≥10 points, complications during hospitalization, and highly-expressed MIR155HG and TNFa were risk factors related to the prognosis of patients. Conclusions: MIR155HG and TNF-a affect the activity of SLE, and the high expressions of them promote the occurrence of such complications as infection, renal damage and cardiac damage, harming the prognosis.

Multi-omics delineate growth factor network underlying exercise effects in an Alzheimer's mouse model.

Physical exercise represents a primary defense against age-related cognitive decline and neurodegenerative disorders like Alzheimer's disease (AD). To impartially investigate the underlying mechanisms, we conducted single-nucleus transcriptomic and chromatin accessibility analyses (snRNA-seq and ATAC-seq) on the hippocampus of mice carrying AD-linked NL-G-F mutations in the amyloid precursor protein gene (APPNL-G-F) following prolonged voluntary wheel-running exercise. Our study reveals that exercise mitigates amyloid-induced changes in both transcriptomic expression and chromatin accessibility through cell type-specific transcriptional regulatory networks. These networks converge on the activation of growth factor signaling pathways, particularly the epidermal growth factor receptor (EGFR) and insulin signaling, correlating with an increased proportion of immature dentate granule cells and oligodendrocytes. Notably, the beneficial effects of exercise on neurocognitive functions can be blocked by pharmacological inhibition of EGFR and the downstream phosphoinositide 3-kinases (PI3K). Furthermore, exercise leads to elevated levels of heparin-binding EGF (HB-EGF) in the blood, and intranasal administration of HB-EGF enhances memory function in sedentary APPNL-G-F mice. These findings offer a panoramic delineation of cell type-specific hippocampal transcriptional networks activated by exercise and suggest EGF-related growth factor signaling as a druggable contributor to exercise-induced memory enhancement, thereby suggesting therapeutic avenues for combatting AD-related cognitive decline.

Alkylide derivatives of diphyllin: synthesis and preliminary anticancer evaluation.

Fourteen diphyllin 4-C-substituted alkylide derivatives were designed and synthesized using a Heck coupling and subsequent hydrogenation reaction. Olefins 3g and 3i exhibited the highest cytotoxicity on breast cancer cell lines MCF-7 with IC50 values of 0.08 and 0.07 µM, and they showed weaker V-ATPase inhibitory potency compared to diphyllin.

Enhanced plant-derived vesicles for nucleotide delivery for cancer therapy.

Small RNAs (microRNAs [miRNAs] or small interfering RNAs [siRNAs]) are effective tools for cancer therapy, but many of the existing carriers for their delivery are limited by low bioavailability, insufficient loading, impaired transport across biological barriers, and low delivery into the tumor microenvironment. Extracellular vesicle (EV)-based communication in mammalian and plant systems is important for many physiological and pathological processes, and EVs show promise as carriers for RNA interference molecules. However, some fundamental issues limit their use, such as insufficient cargo loading and low potential for scaling production. Plant-derived vesicles (PDVs) are membrane-coated vesicles released in the apoplastic fluid of plants that contain biomolecules that play a role in several biological mechanisms. Here, we developed an alternative approach to deliver miRNA for cancer therapy using PDVs. We isolated vesicles from watermelon and formulated a hybrid, exosomal, polymeric system in which PDVs were combined with a dendrimer bound to miRNA146 mimic. Third generation PAMAM was chosen due to its high branching structure and versatility for loading molecules of interest. We performed several in vivo experiments to demonstrate the therapeutic efficacy of our compound and explored in vitro biological mechanisms underlying the anti-tumor effects of miRNA146, which are mostly related to its anti-angiogenic activity.

Hepatic Klf10-Fh1 axis promotes exercise-mediated amelioration of NASH in mice.

Exercise is an effective non-pharmacological strategy for the treatment of nonalcoholic steatohepatitis (NASH), but the underlying mechanism needs further investigation. Kruppel-like factor 10 (Klf10) is a transcriptional factor that is expressed in multiple tissues including liver, whose role in NASH is not well defined. In our study, exercise induces hepatic Klf10 expression through the cAMP/PKA/CREB pathway. Hepatocyte-specific knockout of Klf10 (Klf10LKO) increases lipid accumulation, cell death, inflammation and fibrosis in NASH diet-fed mice and reduces the protective effects of treadmill exercise against NASH, while hepatocyte-specific overexpression of Klf10 (Klf10LTG) works in concert with exercise to reduce NASH in mice. Mechanistically, Klf10 promotes the expression of fumarate hydratase 1 (Fh1), thereby reducing fumarate accumulation in hepatocytes. This decreases the trimethyl (me3) levels of histone 3 lysine 4 (H3K4me3) on lipogenic genes promoters to attenuate lipogenesis, thus ameliorating free fatty acids (FFAs)-induced hepatocytes steatosis, apoptosis, insulin resistance and blunting dysfunctional hepatocytes-mediated activation of macrophages and hepatic stellate cells. Therefore, by regulating the Fh1/fumarate/H3K4me3 pathway, Klf10 acts as a downstream effector of exercise to combat NASH.

Nervogenic Acid Derivatives and Phenanthrenes from Liparis nervosa and Their Antimicrobial and Immunosuppressive Activities.

Two new nervogenic acid derivatives liparisnervosides Q (1) and R (5), as well as five known nervogenic acid derivatives (2-4, 6, 7) and four phenanthrenes (8-11) were isolated from the whole plant of Liparis nervosa (Thunb. ex A. Murray) Lindl.. Their structures were detremined using extensive spectroscopic techniques, including 1D, 2D NMR, and HR-ESI-MS, and acid hydrolysis. Furthermore, their antimicrobial and immunosuppressive activities were evaluated. Nervosine VII (3) exhibited antimicrobial activity against Staphylococcus aureus with an MIC of 62.5 µg/mL and inhibited the proliferation of human T cells with an IC50 value of 9.67±0.96 µM. These findings contribute to our understanding of the potential pharmacological properties of these compounds.

Li Promoting Long Afterglow Organic Light-Emitting Transistor for Memory Optocoupler Module.

The artificial brain is conceived as advanced intelligence technology, capable to emulate in-memory processes occurring in the human brain by integrating synaptic devices. Within this context, improving the functionality of synaptic transistors to increase information processing density in neuromorphic chips is a major challenge in this field. In this article, Li-ion migration promoting long afterglow organic light-emitting transistors, which display exceptional postsynaptic brightness of 7000 cd m-2 under low operational voltages of 10 V is presented. The postsynaptic current of 0.1 mA operating as a built-in threshold switch is implemented as a firing point in these devices. The setting-condition-triggered long afterglow is employed to drive the photoisomerization process of photochromic molecules that mimic neurotransmitter transfer in the human brain for realizing a key memory rule, that is, the transition from long-term memory to permanent memory. The combination of setting-condition-triggered long afterglow with photodiode amplifiers is also processed to emulate the human responding action after the setting-training process. Overall, the successful integration in neuromorphic computing comprising stimulus judgment, photon emission, transition, and encoding,  to emulate the complicated decision tree of the human brain is demonstrated.

Ligand-dependent folding and unfolding dynamics and free energy landscapes of acylphosphatase.

Acylphosphatase (AcP) is an enzyme which catalyses the hydrolysis of acylphosphate. The binding with the phosphate ion (Pi) assumes significance in preserving both the stability and enzymatic activity of AcP. While previous studies using single molecule force spectroscopy explored the mechanical properties of AcP, the influence of Pi on its folding and unfolding dynamic behaviors remains unexplored. In this work, using stable magnetic tweezers, we measured and compared the force-dependent folding and unfolding rates of AcP in the Tris buffer and phosphate buffer within a force range from 2 pN to 40 pN. We found that Pi exerts no discernible effect on the folding dynamics but consistently decreases the force-dependent unfolding rate of AcP by a constant ratio across the entire force spectrum. The free energy landscapes of AcP in the absence and presence of Pi are constructed. Our results reveal that Pi selectively binds to the native state of AcP, stabilizing it and suggesting the general properties of specific ligand-receptor interactions.