Strong chiroptical nonlinearity in coherently stacked boron nitride nanotubes.

Nanomaterials with a large chiroptical response and high structural stability are desirable for advanced miniaturized optical and optoelectronic applications. One-dimensional (1D) nanotubes are robust crystals with inherent and continuously tunable chiral geometries. However, their chiroptical response is typically weak and hard to control, due to the diverse structures of the coaxial tubes. Here we demonstrate that as-grown multiwalled boron nitride nanotubes (BNNTs), featuring coherent-stacking structures including near monochirality, homo-handedness and unipolarity among the component tubes, exhibit a scalable nonlinear chiroptical response. This intrinsic architecture produces a strong nonlinear optical response in individual multiwalled BNNTs, enabling second-harmonic generation (SHG) with a conversion efficiency up to 0.01% and output power at the microwatt level-both excellent figures of merit in the 1D nanomaterials family. We further show that the rich chirality of the nanotubes introduces a controllable nonlinear geometric phase, producing a chirality-dependent SHG circular dichroism with values of -0.7 to +0.7. We envision that our 1D chiral platform will enable novel functions in compact nonlinear light sources and modulators.

Triflic Acid-Promoted 1,2-Amino Migration Reactions in α-Arylaminoacrylamides: Access to Substituted ß-Aminoamides.

A straightforward synthesis of substituted ß-aminoamides from α-arylamino-ß-hydroxyacrylamides, α-arylamino-ß-oxoamides, or their tautomeric mixture has been described. The (E)-enol triflate intermediates are readily generated in situ from these substrates in the presence of triflic anhydride (Tf2O) and triethylamine (Et3N) in a chemoselective manner and undergo triflic acid (TfOH)-promoted cyclization and ring-opening reactions with alcohols to deliver the desired products. The one-pot two-step synthetic protocol features the use of readily available starting materials, mild reaction conditions, high chemoselectivity, operational simplicity, and a wide range of synthetic potential of the products.

Qi Lang formula relieves constipation via targeting SCF/c-kit signaling pathway: An integrated study of network pharmacology and experimental validation.

Background: Constipation is one of the chronic gastrointestinal functional diseases that affects the quality of life. While Qi Lang Formula (QLF) has demonstrated effectiveness in alleviating constipation symptoms, its precise mechanism remains elusive. Methods: QLF was analyzed using UPLC-MS/MS. Targets for QLF were collected from SwissADME, Herb, ITCM databases, and constipation-related targets from scRNA-seq and Genecards databases. Overlapping targets suggested potential QLF therapy targets for constipation. Enrichment analysis used the KOBAS database. A "drug-ingredient-target" network was constructed with Cytoscape, and AutoDock verified active ingredient binding. H&E staining assessed colonic mucosa changes, TEM examined ICC structural changes. ELISA measured neurotransmitter levels, and Western blot verified QLF's effect on target proteins. ICC proliferation was observed through immunofluorescence. Results: We identified 89 targets of QLF associated with ICC-related constipation, with c-Kit emerging as the pivotal target. Molecular docking studies revealed that Atractylenolide Ⅲ, Apigenin, Formononetin, Isorhamnetin, Naringenin, and Ononin exhibited strong binding affinities for the c-Kit structural domain. QLF significantly enhanced first stool passage time, fecal frequency, fecal moisture content, and intestinal propulsion rate. Further analysis unveiled that QLF not only restored neurotransmitter levels but also mitigated colon muscular fiber ruptures. ICC ultrastructure exhibited partial recovery, while Western blot confirmed upregulated c-Kit expression and downstream targets. Immunofluorescence results indicated ICC proliferation post QLF treatment in rat colon. Conclusion: Our findings suggest that QLF may promote ICC proliferation by targeting SCF/c-Kit and its downstream signaling pathway, thereby regulating intestinal motility.

Toward DNN of LUTs: Learning Efficient Image Restoration with Multiple Look-Up Tables.

The widespread usage of high-definition screens on edge devices stimulates a strong demand for efficient image restoration algorithms. The way of caching deep learning models in a look-up table (LUT) is recently introduced to respond to this demand. However, the size of a single LUT grows exponentially with the increase of its indexing capacity, which restricts its receptive field and thus the performance. To overcome this intrinsic limitation of the single-LUT solution, we propose a universal method to construct multiple LUTs like a neural network, termed MuLUT. Firstly, we devise novel complementary indexing patterns, as well as a general implementation for arbitrary patterns, to construct multiple LUTs in parallel. Secondly, we propose a re-indexing mechanism to enable hierarchical indexing between cascaded LUTs. Finally, we introduce channel indexing to allow cross-channel interaction, enabling LUTs to process color channels jointly. In these principled ways, the total size of MuLUT is linear to its indexing capacity, yielding a practical solution to obtain superior performance with the enlarged receptive field. We examine the advantage of MuLUT on various image restoration tasks, including super-resolution, demosaicing, denoising, and deblocking. MuLUT achieves a significant improvement over the single-LUT solution, e.g., up to 1.1dB PSNR for super-resolution and up to 2.8dB PSNR for grayscale denoising, while preserving its efficiency, which is 100× less in energy cost compared with lightweight deep neural networks. Our code and trained models are publicly available at https://github.com/ddlee-cn/MuLUT.

Insights into the role of adipose-derived stem cells and secretome: potential biology and clinical applications in hypertrophic scarring.

Scar tissue is the inevitable result of repairing human skin after it has been subjected to external destructive stimuli. It leads to localized damage to the appearance of the skin, accompanied by symptoms such as itching and pain, which reduces the quality of life of the patient and causes serious medical burdens. With the continuous development of economy and society, there is an increasing demand for beauty. People are looking forward to a safer and more effective method to eliminate pathological scarring. In recent years, adipose-derived stem cells (ADSCs) have received increasing attention from researchers. It can effectively improve pathological scarring by mediating inflammation, regulating fibroblast proliferation and activation, and vascular reconstruction. This review focuses on the pathophysiological mechanisms of hypertrophic scarring, summarizing the therapeutic effects of in vitro, in vivo, and clinical studies on the therapeutic effects of ADSCs in the field of hypertrophic scarring prevention and treatment, the latest application techniques, such as cell-free therapies utilizing ADSCs, and discussing the advantages and limitations of ADSCs. Through this review, we hope to further understand the characterization of ADSC and clarify the effectiveness of its application in hypertrophic scarring treatment, so as to provide clinical guidance.

Scale-Aware Edge-Preserving Full Waveform Inversion with Diffusion Filter for Crosshole Sensor Arrays.

Full waveform inversion (FWI) is recognized as a leading data-fitting methodology, leveraging the detailed information contained in physical waveform data to construct accurate, high-resolution velocity models essential for crosshole surveys. Despite its effectiveness, FWI is often challenged by its sensitivity to data quality and inherent nonlinearity, which can lead to instability and the inadvertent incorporation of noise and extraneous data into inversion models. To address these challenges, we introduce the scale-aware edge-preserving FWI (SAEP-FWI) technique, which integrates a cutting-edge nonlinear anisotropic hybrid diffusion (NAHD) filter within the gradient computation process. This innovative filter effectively reduces noise while simultaneously enhancing critical small-scale structures and edges, significantly improving the fidelity and convergence of the FWI inversion results. The application of SAEP-FWI across a variety of experimental and authentic crosshole datasets clearly demonstrates its effectiveness in suppressing noise and preserving key scale-aware and edge-delineating features, ultimately leading to clear inversion outcomes. Comparative analyses with other FWI methods highlight the performance of our technique, showcasing its ability to produce images of notably higher quality. This improvement offers a robust solution that enhances the accuracy of subsurface imaging.

Intralesional curettage and surgical adjuvants in the treatment of giant cell tumor of bone: meta-analysis and systematic review.

BACKGROUND: The ideal treatment for giant cell tumor of bone (GCTB) is still controversial. Various surgical adjuvants have been introduced following intralesional curettage to improve local control rates. However, findings from relevant studies are inconsistent, and no consensus has been reached. The purpose of this study is to determine what intraoperative adjuvant is effective in decreasing the recurrence of GCTB. METHODS: We performed a systematic review and meta-analysis of articles published in the PubMed and Embase electronic databases which assessed the recurrence rate of GCTB following intralesional curettage with or without various surgical adjuvants. Two authors independently evaluated all publications. Meta-analysis was performed with Stata/MP (Version 17.0, StataCorp LLC, TX, USA) and Review Manager (RevMan, Version 5.4.1, The Cochrane Collaboration, 2020). Pooled risk ratio (RR) was used for analysis, with P values less than 0.05 considered statistically significant. RESULTS: Twenty-four studies involving 2,579 patients were included in this analysis. The overall recurrence rates for patients treated with or without high-speed burring (HSB) are 11.9% (26/218) and 47.7% (92/193), respectively. The pooled RR for tumor recurrence is 0.33 (95% CI: 0.22 to 0.49, P<0.001). In the meanwhile, the overall recurrence rates for patients treated with or without chemical adjuvants are 23.5% (77/328) and 26.1% (73/280), respectively, with a pooled RR of 0.84 (95% CI: 0.63 to 1.10, P=0.89). Additionally, the overall recurrence rates for patients treated with or without polymethyl methacrylate (PMMA) are 20.4% (205/1,006) and 33.4% (314/939), respectively, with a pooled RR of 0.59 (95% CI: 0.50 to 0.69, P<0.001). CONCLUSIONS: Intraoperative application of HSB or PMMA has an additional antitumor effect, while the use of phenol or H2O2 fails to make any significant difference (PROSPERO: CRD42022344262).

Direct reprogramming of fibroblasts into functional hepatocytes via CRISPRa activation of endogenous Gata4 and Foxa3.

BACKGROUND: The ability to generate functional hepatocytes without relying on donor liver organs holds significant therapeutic promise in the fields of regenerative medicine and potential liver disease treatments. Clustered regularly interspaced short palindromic repeats (CRISPR) activator (CRISPRa) is a powerful tool that can conveniently and efficiently activate the expression of multiple endogenous genes simultaneously, providing a new strategy for cell fate determination. The main purpose of this study is to explore the feasibility of applying CRISPRa for hepatocyte reprogramming and its application in the treatment of mouse liver fibrosis. METHOD: The differentiation of mouse embryonic fibroblasts (MEFs) into functional induced hepatocyte-like cells (iHeps) was achieved by utilizing the CRISPRa synergistic activation mediator (SAM) system, which drove the combined expression of three endogenous transcription factors-Gata4, Foxa3, and Hnf1a-or alternatively, the expression of two transcription factors, Gata4 and Foxa3. In vivo, we injected adeno-associated virus serotype 6 (AAV6) carrying the CRISPRa SAM system into liver fibrotic Col1a1-CreER; Cas9fl/fl mice, effectively activating the expression of endogenous Gata4 and Foxa3 in fibroblasts. The endogenous transcriptional activation of genes was confirmed using real-time quantitative polymerase chain reaction (RT-qPCR) and RNA-seq, and the morphology and characteristics of the induced hepatocytes were observed through microscopy. The level of hepatocyte reprogramming in vivo is detected by immunofluorescence staining, while the improvement of liver fibrosis is evaluated through Sirius red staining, alpha-smooth muscle actin (α-SMA) immunofluorescence staining, and blood alanine aminotransferase (ALT) examination. RESULTS: Activation of only two factors, Gata4 and Foxa3, via CRISPRa was sufficient to successfully induce the transformation of MEFs into iHeps. These iHeps could be expanded in vitro and displayed functional characteristics similar to those of mature hepatocytes, such as drug metabolism and glycogen storage. Additionally, AAV6-based delivery of the CRISPRa SAM system effectively induced the hepatic reprogramming from fibroblasts in mice with live fibrosis. After 8 weeks of induction, the reprogrammed hepatocytes comprised 0.87% of the total hepatocyte population in the mice, significantly reducing liver fibrosis. CONCLUSION: CRISPRa-induced hepatocyte reprogramming may be a promising strategy for generating functional hepatocytes and treating liver fibrosis caused by hepatic diseases.

Ursolic acid targets secreted phosphoprotein 1 to regulate Th17 cells against non-alcoholic fatty liver disease.

Background/Aims: Non-alcoholic fatty liver disease (NAFLD) has become an increasingly important health challenge, with a substantial rise linked to changing lifestyles and global obesity. Ursolic acid, a natural pentacyclic triterpenoid, has been explored for its potential therapeutic effects. Given its multifunctional bioactive properties, this research further revealed the pharmacological mechanisms of ursolic acid on NAFLD. Methods: Drug target chips and bioinformatics analysis were combined in this study to explore the potential therapeutic effects of ursolic acid on NAFLD. Molecular docking simulations, surface plasmon resonance analyses, pull-down experiments, and co-immunoprecipitation assays were used to verify the direct interactions. Gene knockdown mice were generated, and high-fat diets were used to validate drug efficacy. Furthermore, initial CD4+ T cells were isolated and stimulated to demonstrate our findings. Results: In this study, the multifunctional extracellular matrix phosphorylated glycoprotein secreted phosphoprotein 1 (SPP1) was investigated, highlighting its capability to induce Th17 cell differentiation, amplifying inflammatory cascades, and subsequently promoting the evolution of NAFLD. In addition, this study revealed that in addition to the canonical TGF-ß/IL-6 cytokine pathway, SPP1 can directly interact with ITGB1 and CD44, orchestrating Th17 cell differentiation via their joint downstream ERK signaling pathway. Remarkably, ursolic acid intervention notably suppressed the protein activity of SPP1, suggesting a promising avenue for ameliorating the immunoinflammatory trajectory in NAFLD progression. Conclusions: Ursolic acid could improve immune inflammation in NAFLD by modulating SPP1-mediated Th17 cell differentiation via the ERK signaling pathway, which is orchestrated jointly by ITGB1 and CD44, emerging as a linchpin in this molecular cascade.

Constructing network structures to enhance stability and target deposition of selenium nanoparticles via amphiphilic sodium alginate and alkyl glycosides.

Dietary selenium (Se) supplementation has recently received increasing attention; however, Selenium nanoparticles (SeNPs) exhibit poor stability and tend to aggregate in aqueous solution. Therefore, enhancing the stability of SeNPs and their effective delivery to plants remain challenging. In this study, sodium alginate (SA) and lysozyme (LZ) were reacted via the wet-heat Maillard reaction (MR) to obtain amphiphilic alginate-based polymers (SA-LZ). Alkyl glycosides (APG) were introduced into SA-LZ to enhance the deposition of SeNPs in leaves. Thus, a renewable and degradable polysaccharide-based material (SA-LZ/APG) loaded with Se formed an amphiphilic alginate-based-based shell with a Se core. Notably, the encapsulation of SeNPs into a polysaccharide base (SA-LZ/APG) increased the stabilization of SeNPs and resulted in orange-red, zero-valent, monoclinic and spherical SeNPs with a mean diameter of approximately 43.0 nm. In addition, SA-LZ/APG-SeNPs reduced the interfacial tension of plant leaves and increased the Se content of plants compared to the blank group. In vitro studies have reported that SA-LZ/APG-SeNPs and SA-LZ-SeNPs have significantly better clearance of DDPH and ABTS than that of APG-SeNPs. Thus, we believe that SA-LZ/APG is a promising smart delivery system that can synergistically enhance the stability of SeNPs in aqueous solutions and improve the bioavailability of Se nutrient solutions.

Enhanced PSO feature selection with Runge-Kutta and Gaussian sampling for precise gastric cancer recurrence prediction.

Gastric cancer (GC), characterized by its inconspicuous initial symptoms and rapid invasiveness, presents a formidable challenge. Overlooking postoperative intervention opportunities may result in the dissemination of tumors to adjacent areas and distant organs, thereby substantially diminishing prospects for patient survival. Consequently, the prompt recognition and management of GC postoperative recurrence emerge as a matter of paramount urgency to mitigate the deleterious implications of the ailment. This study proposes an enhanced feature selection model, bRSPSO-FKNN, integrating boosted particle swarm optimization (RSPSO) with fuzzy k-nearest neighbor (FKNN), for predicting GC. It incorporates the Runge-Kutta search, for improved model accuracy, and Gaussian sampling, enhancing the search performance and helping to avoid locally optimal solutions. It outperforms the sophisticated variants of particle swarm optimization when evaluated in the CEC 2014 test suite. Furthermore, the bRSPSO-FKNN feature selection model was introduced for GC recurrence prediction analysis, achieving up to 82.082 % and 86.185 % accuracy and specificity, respectively. In summation, this model attains a notable level of precision, poised to ameliorate the early warning system for GC recurrence and, in turn, advance therapeutic options for afflicted patients.

Synthesis and Characterization of Superhydrophobic Epoxy Resin Coating with SiO2@CuO/HDTMS for Enhanced Self-Cleaning, Photocatalytic, and Corrosion-Resistant Properties.

The exceptional corrosion resistance and combined physical and chemical self-cleaning capabilities of superhydrophobic photocatalytic coatings have sparked significant interest among researchers. In this paper, we propose an economical and eco-friendly superhydrophobic epoxy resin coating that incorporates SiO2@CuO/HDTMS nanoparticles modified with Hexadecyltrimethoxysilane (HDTMS). The application of superhydrophobic coatings effectively reduces the contact area between the metal surface and corrosive media, leading to a decreased corrosion rate. Additionally, the incorporation of nanomaterials, exemplified by SiO2@CuO core-shell nanoparticles, improves the adhesion and durability of the coatings on aluminum alloy substrates. Experimental data from Tafel curve analysis and electrochemical impedance spectroscopy (EIS) confirm the superior corrosion resistance of the superhydrophobic modified aluminum alloy surface compared to untreated surfaces. Estimations indicate a significant reduction in corrosion rate after superhydrophobic treatment. Furthermore, an optical absorption spectra analysis of the core-shell nanoparticles demonstrates their suitability for photocatalytic applications, showcasing their potential contribution to enhancing the overall performance of the coated surfaces. This research underscores the promising approach of combining superhydrophobic properties with photocatalytic capabilities to develop advanced surface modification techniques for enhanced corrosion resistance and functional properties in diverse industrial settings.

The value of speckle-tracking stratified strain combined with myocardial work measurement in evaluating left ventricular function in patients with heart failure with preserved ejection fraction.

Background: Heart failure with preserved ejection fraction (HFpEF) is a highly prevalent progressive disease accompanied by poor quality of life, high utilization of medical resources, morbidity, and mortality. However, the role of left ventricular (LV) systolic dysfunction has yet to be well elaborated despite the preservation of the LV ejection fraction. This study aimed to explore the diagnostic value of speckle-tracking stratified strain combined with myocardial work (MW) measurement in evaluating LV systolic dysfunction in patients with HFpEF. Methods: A total of 125 study consecutive individuals, 64 HFpEF patients, and 61 controls were prospectively enrolled in the Fourth Affiliated Hospital of Harbin Medical University. In addition to the conventional echocardiographic parameters, LV stratified strain and MW parameters were statistically compared between the HFpEF and control groups. The global longitudinal strain (GLS) of the subendocardium, myocardium, and subepicardium (GLSendo, GLSmyo, and GLSepi); the transmural gradient (ΔGLS); the global myocardial work index (GWI), global myocardial work efficiency (GWE), global myocardial constructive work (GCW), and the global myocardial wasted work (GWW) were included. Area under the receiver operating characteristic curve analysis was used to evaluate the diagnostic performance of these univariate and multivariable logistic models in detecting impaired LV systolic function in HFpEF. Ten-fold cross-validation was used to evaluate the generalizability of the predictive model. Results: Stratified strains values showed a gradient decline from GLSendo to GLSepi in both control and HFpEF patients. Compared with the control group, HFpEF patients had a significantly reduced GLSepi, GLSmyo, GLSendo, ΔGLS, GWI, GWE, and GCW and a significantly increased GWW (all P<0.001). In the derivation set, the optimal logistic model (combined stratified strain and MW variables) demonstrated the highest performance in predicting LV systolic function impairment in HFpEF patients. The best-performing model with a mean area under the curve (AUC) of 0.966 [95% confidence interval (CI): 0.88 to 1] accessed by 10-fold cross-validation. In the validation set, the AUC of the optimal logistic model was 0.933 (95% CI: 0.85 to 1), the sensitivity was 87%, and the specificity was 93%. Conclusions: Both speck-tracking stratified strain and MW measurement may sensitively detect impairment of LV myocardial function at an early stage for patients with HFpEF. Combining the two techniques may improve the quality of HFpEF diagnosis and may provide a reference value for the early diagnosis of HFpEF in the future.

Differential Microbial Composition and Interkingdom Interactions in the Intestinal Microbiota of Holstein and German Simmental × Holstein Cross F1 Calves: A Comprehensive Analysis of Bacterial and Fungal Diversity.

Calf intestines are colonized by rich and complex microbial communities, playing a crucial role in animal physiology, metabolism, nutrition, and immune function. In this study, we provide insight into the composition of fecal microbial bacteria and fungi, respectively, as well as the cross-kingdom interactions. We investigated the intestinal microbiota of different breeds of calves by characterizing the bacterial and fungal communities in the rectal feces of Holstein calves and German Simmental × Holstein cross F1 generation (GXH) using 16S rRNA and ITS amplicon sequencing techniques. PICRUSt2 (version 2.2.0) were used to determine microbial diversity and function and explore the reasons why Holstein calves are more susceptible to diarrhea. The results revealed no significant difference in the diversity of fecal microbiota among the groups (p > 0.05). We identified Firmicutes, Bacteroidetes, and Proteobacteria as the dominant bacterial phyla in the fecal bacterial communities of the two breeds of calves. Ascomycota and Basidiomycota play important roles in the fungal community but differ in relative abundance. Bacteroides was the dominant genus at the group level for calf fecal microbiota in both breeds. The relative abundance of Prevotella, Escherichia-Shigella, Peptostreptococcus, and Butyricicoccus was higher in Holstein calves, and the relative abundance of Faecalibacterium, Megamonas, Butyricicoccus, and Alloprevotella was lower than GXH group. Aspergillus and Cladosporium were the dominating genera of fecal fungi in both groups of calves. LEfSe analysis revealed 33 different bacteria and 23 different fungi between the two groups, with more differential strains found in GXH. In addition, the feces fungi-bacteria interkingdom interactions varied among breeds. Thus, the composition and structure of bacterial and fungal communities in calf feces varied by breed, indicating a potential association between breed and microbial communities. We also found differences in the network between bacterial-fungal kingdoms. We explain the reasons for Holstein calves being more prone to diarrhea. This indicated that breed makes differences in calf diarrhea rates by influencing gut microbial composition and interactions.

B ← N coordination bond reinforced dynamic fluorescence of pH-responsive amphiphile alginate aggregates for anti-counterfeiting.

High quantum yield polysaccharide-based materials are significative for the dynamic anti-counterfeiting, while that are limited by weak fluorescence. However, natural polysaccharides with weak fluorescence are not suitable for anti-counterfeiting. Herein, alginate derivatives (SA-PBA) exhibiting aggregation-induced emission with high-quantum yields were synthesized by grafting phenylboronic acid (PBA) onto a sodium alginate (SA) chain. As the concentration increases, polymer assembly can be induced to form more compact soft colloidal aggregates, which enhances the fluorescence properties of alginate derivatives by introducing B â† N coordination bonds in the hydrophobic microregions. Interestingly, the clustered aggregates of SA-PBA can be dynamically controlled by pH, realizing the reversible adjustment of fluorescence. The corresponding mechanism is revealed by the combination of coarse-grained simulations and experiments. It is found that SA-PBA uses a hydrophobic driving force and hydrogen bond interaction to self-assemble in an aqueous solution and promote fluorescence emission. Moreover, the fluorescence quantum yield of SA-PBA can reach 14.4 % and can be reversibly altered by tuning soft colloidal microstructures. Therefore, a reversible information encryption system of SA-PBA is developed for anti-counterfeiting. This work shed some light on how to design novel anti-counterfeit materials based on natural polysaccharides and optimize the dynamic fluorescence conditions.

Uncovering PROTAC Sensitivity and Efficacy by Multidimensional Proteome Profiling: A Case for STAT3.

Proteolysis-targeting chimera (PROTAC) is a powerful technology that can effectively trigger the degradation of target proteins. The intricate interplay among various factors leads to a heterogeneous drug response, bringing about significant challenges in comprehending drug mechanisms. Our study applied data-independent acquisition-based mass spectrometry to multidimensional proteome profiling of PROTAC (DIA-MPP) to uncover the efficacy and sensitivity of the PROTAC compound. We profiled the signal transducer and activator of transcription 3 (STAT3) PROTAC degrader in six leukemia and lymphoma cell lines under multiple conditions, demonstrating the pharmacodynamic properties and downstream biological responses. Through comparison between sensitive and insensitive cell lines, we revealed that STAT1 can be regarded as a biomarker for STAT3 PROTAC degrader, which was validated in cells, patient-derived organoids, and mouse models. These results set an example for a comprehensive description of the multidimensional PROTAC pharmacodynamic response and PROTAC drug sensitivity biomarker exploration.

Pyruvate kinase deficiency and PKLR gene mutations: Insights from molecular dynamics simulation analysis.

Pyruvate kinase deficiency is a rare hereditary erythrocyte enzyme disease caused by mutations in the pyruvate kinase liver and red blood cell gene. The clinical presentations of pyruvate kinase deficiency are significantly heterogeneous, ranging from just mild anemia to hemolytic crisis or even death. The proband in our study was a 2-year-old girl for severe skin and scleral icterus with progressive aggravation. We collected the family's data for further analysis. Whole exome genome sequencing of the pedigree revealed a novel compound heterozygous mutation, c.1097del (p.P366Lfs*12) and c.1493G > A (p.R498H), in the pyruvate kinase liver and red blood cell gene. Furthermore, molecular dynamics simulations were employed to uncover differences between the wild type and mutant pyruvate kinase liver and red blood cell proteins, focusing on structural stability, protein flexibility, secondary structure, and overall conformation. The combined bioinformatic tools were also utilised to assess the effects of the missense mutation on protein function. Thereafter, wild type and mutant plasmids were constructed and transfected into 293T cells, and Western blot assay was conducted to validate the impact of the mutations on the expression of pyruvate kinase liver and red blood cell protein. The data presented in our study enriches the genotype database and provides evidence for genetic counseling and molecular diagnosis of pyruvate kinase deficiency.