Association of Cadherin-Related Family Member 1 with Traumatic Brain Injury.

The cadherin family plays a pivotal role in orchestrating synapse formation in the central nervous system. Cadherin-related family member 1 (CDHR1) is a photoreceptor-specific calmodulin belonging to the expansive cadherin superfamily. However, its role in traumatic brain injury (TBI) remains largely unknown. CDHR1 expression across various brain tissue sites was analyzed using the GSE104687 dataset. Employing a summary-data-based Mendelian Randomization (SMR) approach, integrated analyses were performed by amalgamating genome-wide association study abstracts from TBI with public data on expressed quantitative trait loci and DNA methylation QTL from both blood and diverse brain tissues. CDHR1 expression and localization in different brain tissues were meticulously delineated using western blotting, immunohistochemistry, and enzyme-linked immunosorbent assay. CDHR1 expression was consistently elevated in the TBI group compared to that in the sham group across multiple tissues. The inflammatory response emerged as a crucial biological mechanism, and pro-inflammatory and anti-inflammatory factors were not expressed in either group. Integrated SMR analyses encompassing both blood and brain tissues substantiated the heightened CDHR1 expression profiles, with methylation modifications emerging as potential contributing factors for increased TBI risk. This was corroborated by western blotting and immunohistochemistry, confirming augmented CDHR1 expression following TBI. This multi-omics-based genetic association study highlights the elevated TBI risk associated with CDHR1 expression coupled with putative methylation modifications. These findings provide compelling evidence for future targeted investigations and offer promising avenues for developing interventional therapies for TBI.

[Effects of Different Nutritional Scoring Systems on Prognosis of Elderly Patients with Multiple Myeloma].

OBJECTIVE: To analyze the prognostic nutritional index (PNI), controlling nutritional status (CONUT) and fibrinogen/albumin ratio (FAR) levels in elderly patients with multiple myeloma (MM) and their prognostic impact. METHODS: The clinical data of 74 elderly MM patients diagnosed in Gansu Provincial Hospital from January 2020 to July 2022 were retrospectively analyzed. The optimal cut-off values for PNI, CONUT score and FAR were obtained by receiver operating characteristic (ROC) curve, which were used for grouping patients. The correlation of above three indexes with clinical parameters such as sex, serum calcium (Ca), ß2-microglobulin (ß2-MG), serum creatinine (Cr) in elderly MM patients were analyzed. The survival rates of patients with different levels of each index were compared. Univariate and multivariate analysis of the impact of clinical indicators on the prognosis of patients were performed. RESULTS: The optimal cut-off values for PNI, CONUT score and FAR were 39.775, 3.5 and 0.175, respectively, according to which the patients were divided into high and low group. Statistical analysis showed that there were significant differences in albumin level among different groups (all P < 0.05). In addition, there was a significant difference in hemoglobin between high-PNI group and low-PNI group (P < 0.05), while in sex distribution between high-FAR and low-FAR group (P < 0.05). The survival rate of elderly MM patients with increased PNI, decreased CONUT score and FAR was higher (all P < 0.05). Univariate and multivariate analysis showed that ß2-MG, Cr, PNI, CONUT score and FAR were independent prognostic factors for elderly MM patients. CONCLUSION: PNI, CONUT score and FAR are related to some clinical indicators of elderly MM patients, and have an impact on the prognosis.

Association of Frailty with Patient-Report Outcomes and Major Clinical Determinants in Patients with Acute Exacerbation of Chronic Obstructive Pulmonary Disease.

Purpose: This study aimed to explore the correlation of frailty status with disease characteristics and patient-reported outcomes (PROs) in patients with acute exacerbations of chronic obstructive pulmonary disease (AECOPD) and determine the sensitivity and specificity of modified COPD PRO scale (mCOPD-PRO) for detecting frailty. Patients and Methods: This cross-sectional study surveyed 315 inpatients with AECOPD from a tertiary hospital in China from August 2022 to June 2023. Patient frailty and PROs were assessed using the validated FRAIL scale and mCOPD-PRO, respectively. Spearman's ρ was used to assess the relevance of lung disease indicators commonly used in clinical practice, and ordinal logistic regression analyses were used to identify the variables associated with frailty status. The validity of mCOPD-PRO in discriminating frail or non-frail individuals was determined using the receiver operating characteristic curve. Results: The participants (N=302, mean age 72.4±9.1 years) were predominantly males (73.2%). Among them, 43 (14.3%) patients were not frail, whereas 123 (40.7%) and 136 (45.0%) patients were pre-frail and frail, respectively. The FRAIL scale was moderately correlated with the mCOPD-PRO scores (Spearman's rank correlation coefficient [Rs]=0.52, P<0.01) for all dimensions (Rs=0.43-0.49, P<0.01). Patients residing in rural areas (odds ratio [OR], 1.67; 95% confidence interval [95% CI], 1.01-2.76) and with higher mCOPD-PRO scores (OR, 4.78; 95% CI, 2.75-8.32) were more likely to be frail. Physically active patients (OR, 0.42; 95% CI, 0.21-0.84) were less likely to be frail. In addition, mCOPD-PRO had good discriminate validity for detecting frailty (area under the curve=0.78), with a sensitivity and specificity of 84.6% and 60.8%, respectively. The optimal probability threshold for mCOPD-PRO was ≥1.52 points. Conclusion: In patients with AECOPD, frailty is closely related to PROs and disease characteristics. Additionally, the mCOPD-PRO score can distinguish well between frail and non-frail patients. Our findings provide support for interventions targeting frail populations with AECOPD.

Patients with chronic obstructive pulmonary disease often have concomitant frailty that may lead to disease deterioration such as acute exacerbations, hospital readmissions, disability, and premature death. Patient-reported outcomes are often used in clinical practice to measure patients' disease characteristics and overall status. Whether patients' frailty state is associated with patient-reported outcomes and if so, which factors are associated with frailty remain unclear. This study, conducted in China, examined their relationship as well as identified factors associated with frailty states. 302 hospitalized patients with acute exacerbations of chronic obstructive pulmonary disease completed a questionnaire answering questions about disease severity, frailty state, anxiety, and depression. The findings suggest that people who live in rural areas, self-reported more severe overall conditions, and are physically inactive are more likely to be frail. Patient-reported outcomes can distinguish between frail and non-frail patients. Therefore, patient-reported outcomes can be used to assess the extent of frailty; early screening of AECOPD combined frailty population and implementation of interventions can help mitigate the adverse effects of frailty.

Landslide susceptibility assessment based on frequency ratio and semi-supervised heterogeneous ensemble learning model.

Epistemic uncertainty in data-driven landslide susceptibility assessment often tends to be increased by the limited accuracy of an individual model, as well as uncertainties associated with the selection of non-landslide samples. To address these issues, this paper centers on the landslide disaster in Ji'an City, China, and proposes a heterogeneous ensemble learning method incorporating frequency ratio (FR) and semi-supervised sample expansion. Based on the superimposed results of 12 environmental factor frequency ratios (FFR), non-landslide samples were selected and input into light gradient boosting machine (LightGBM), random forest (RF), and convolutional neural network (CNN) models for prediction along with historical landslide samples. The predicted probability values are integrated by four heterogeneous ensemble strategies to expand samples from high-confidence results. The model's performance is evaluated using the area under the receiver operating characteristic curve (AUC), partition frequency ratio (PFR), and other verification methods. The results demonstrate that the negative sample based on FFR sampling is more accurate than the random sampling method, and the FR-SSELR model based on frequency ratio sampling and semi-supervised ensemble strategy exhibits the highest performance (AUC = 0.971, ACC = 0.941). A more reasonable landslide susceptibility map was drawn based on this model, with the lowest percentage of landslides in the low and very low susceptibility zones (sum of PFR = 0.194), as well as the highest percentage of landslides in the high and very high susceptibility zones (sum of PFR = 6.800). Furthermore, the FR-SSELR model improved economic benefits by 3.82-14.2%, offering valuable guidance for decision-making regarding landslide management and the sustainability of Ji'an City.

The natural polycyclic tetramate macrolactam HSAF inhibit Fusarium graminearum through altering cell membrane integrity by targeting FgORP1.

Fusarium graminearum is a dominant phytopathogenic fungus causing Fusarium head blight (FHB) in cereal crops. Heat-stable antifungal factor (HSAF) is a polycyclic tetramate macrolactam (PoTeM) isolated from Lysobacter enzymogenes that exhibits strong antifungal activity against F. graminearum. HSAF significantly reduces the DON production and virulence of F. graminearum. Importantly, HSAF exhibited no cross-resistance to carbendazim, phenamacril, tebuconazole and pydiflumetofen. However, the target protein of HSAF in F. graminearum is unclear. In this study, the oxysterol-binding protein FgORP1 was identified as the potential target of HSAF using surface plasmon resonance (SPR) combined with RNA-sequence (RNA-seq). The RNA-seq results showed cell membrane and ergosterol biosynthesis were significantly impacted by HSAF in F. graminearum. Molecular docking showed that HSAF binds with arginine 1205 and glutamic acid 1212, which are located in the oxysterol-binding domain of FgORP1. The two amino acids in FgORP1 are responsible for HSAF resistance in F. graminearum though site-directed mutagenesis. Furthermore, deletion of FgORP1 led to significantly decreased sensitivity to HSAF. Additionally, FgORP1 regulates the mycelial growth, conidiation, DON production, ergosterol biosynthesis and virulence in F. graminearum. Overall, our findings revealed the mode of action of HSAF against F. graminearum, indicating that HSAF is a promising fungicide for controlling FHB.

Highly branched bolapolyphilic liquid crystals with a cubic A15 network at the triangle-square transition.

Rod-like bolapolyphiles with highly branched carbosilane-based side-chains self-assemble into several honeycomb structures if the oligo(p-phenylene ethynylene) core is polyfluorinated, whereas for the non-fluorinated series an A15 type cubic network of rod-bundles was observed instead, suggesting a brand new pathway for the transition between triangular and square honeycomb phases.

A multi-resolution TOF-DOI detector for human brain dedicated PET scanner.

Objective. We propose a single-ended readout, multi-resolution detector design that can achieve high spatial, depth-of-interaction (DOI), and time-of-flight (TOF) resolutions, as well as high sensitivity for human brain-dedicated positron emission tomography (PET) scanners.Approach. The detector comprised two layers of LYSO crystal arrays and a lightguide in between. The top (gamma ray entrance) layer consisted of a 16 × 16 array of 1.53 × 1.53 × 6 mm3LYSO crystals for providing high spatial resolution. The bottom layer consisted of an 8 × 8 array of 3.0 × 3.0 × 15 mm3LYSO crystals that were one-to-one coupled to an 8 × 8 multipixel photon counter (MPPC) array for providing high TOF resolution. The 2 mm thick lightguide introduces inter-crystal light sharing that causes variations of the light distribution patterns for high DOI resolution. The detector was read out by a PETsys TOFPET2 application-specific integrated circuit.Main result. The top and bottom layers were distinguished by a convolutional neural network with 97% accuracy. All crystals in the top and bottom layers were resolved. The inter-crystal scatter (ICS) events in the bottom layer were identified, and the measured average DOI resolution of the bottom layer was 4.1 mm. The coincidence time resolution (CTR) for the top-top, top-bottom, and bottom-bottom coincidences was 476 ps, 405 ps, and 298 ps, respectively. When ICS events were excluded from the bottom layer, the CTR of the bottom-bottom coincidence was 277 ps.Significance. The top layer of the proposed two-layer detector achieved a high spatial resolution and the bottom layer achieved a high TOF resolution. Together with its high DOI resolution and detection efficiency, the proposed detector is well suited for next-generation high-performance brain-dedicated PET scanners.

Association between triglyceride glucose index and all-cause mortality in patients with cerebrovascular disease: a retrospective study.

BACKGROUND: Triglyceride glucose (TyG) is associated with stroke, atherosclerosis, and adverse clinical outcomes. However, its correlation with cerebrovascular disease (CVD) mortality remains unclear. This study aimed to investigate the relationship between TyG index and mortality in patients with CVD. METHODS: Patient data sourced from the Medical Information Mart for Intensive Care -IV database were categorized based on TyG quartiles. Kaplan-Meier survival analysis was used to estimate survival disparities among the TyG subgroups. Cox proportional risk modeling was used to examine the association between the TyG index and mortality. Generalized summation models were applied to fit the smoothed curves. log-likelihood ratio test were used to analyze the non-linear relationship. RESULTS: The study comprised 1,965 patients (50.18% were male). The 28-day and 90-day mortality rates were 20.10% and 24.48%, respectively. The TyG index exhibited a linear relationship with the 28-day mortality (Hazards ratio (HR), 1.16; 95% confidence interval (CI), 0.99-1.36) and the 90-day mortality (HR, 1.18; 95% CI, 1.02-1.37). In the TyG Q4 group, each 1 mg/dl increase was linked to a 35% rise in the risk of 28-day mortality and a 38% increase in the risk of 90-day mortality. Subgroup analyses highlighted a more substantial association between TyG index and 90-day mortality in the diabetic group. CONCLUSION: Our findings underscore the positive association between TyG and the 28- and 90-day mortality rates in patients with CVD. This insight may prove pivotal for identifying at-risk populations and enhancing risk prediction in the clinical management of CVD.

Knockdown of LCN2 Attenuates Brain Injury After Intracerebral Hemorrhage via Suppressing Pyroptosis.

Objective: The aims of this study are to screen novel differentially expressed genes (DEGs) for intracerebral hemorrhage (ICH) and reveal the role of Lipocalin-2 (LCN2) in ICH. Methods: We constructed the ICH model by injection of autologous whole blood into the right basal ganglia in rats. RNA-sequencing and bioinformatics analyses were performed to identify the DEGs between ICH and sham rats, and some important ones were confirmed using quantitative real-time PCR (qRT-PCR). LCN shRNA was used to knockdown of LCN2 in ICH rats. Pathological examination was carried out using 2,3,5-triphenyltetrazolium chloride (TTC) staining and Hematoxylin-eosin (HE) staining. Immunohistochemistry detected Caspase-3, and co-staining of Terminal dUTP nick end labeling (TUNEL) and NEUN staining were performed for neuron apoptosis assessment. Western blot analysis was performed to quantify pyroptosis-related proteins. Enzyme-linked immunosorbent assay (ELISA) was used to measure inflammatory cytokine levels. Results: ICH rats exhibited significant hematomas, higher brain water content, obvious interstitial edema, and inflammatory infiltration, as well as more apoptotic cells in brain tissues. RNA-seq analysis identified 103 upregulated and 81 downregulated DEGs. The expression of LCN2, HSPB1, CXCL10, and MEF2B were upregulated in ICH rats. ICH triggered the release of interleukin (IL)-1ß, tumor necrosis factor-α (TNF-α), and IL-18, and promoted the expression of pyroptosis-related proteins Caspase-1, GSDMD, NLRP3, and ASC. LCN2 knockdown attenuated the pathological characteristics of ICH, and also reduced pyroptosis in brain tissues. Conclusion: Inhibition of LCN2 attenuates brain injury after ICH via suppressing pyroptosis, which provide guidance for ICH management.

Utilizing a novel model of PANoptosis-related genes for enhanced prognosis and immune status prediction in kidney renal clear cell carcinoma.

Kidney renal clear cell carcinoma (KIRC) is the most common histopathologic type of renal cell carcinoma. PANoptosis, a cell death pathway that involves an interplay between pyroptosis, apoptosis and necroptosis, is associated with cancer immunity and development. However, the prognostic significance of PANoptosis in KIRC remains unclear. RNA-sequencing expression and mutational profiles from 532 KIRC samples and 72 normal samples with sufficient clinical data were retrieved from the Cancer Genome Atlas (TCGA) database. A prognostic model was constructed using differentially expressed genes (DEGs) related to PANoptosis in the TCGA cohort and was validated in a Gene Expression Omnibus (GEO) cohorts. Incorporating various clinical features, the risk model remained an independent prognostic factor in multivariate analysis, and it demonstrated superior performance compared to unsupervised clustering of the 21 PANoptosis-related genes alone. Further mutational analysis showed fewer VHL and more BAP1 alterations in the high-risk group, with alterations in both genes also associated with patient prognosis. The high-risk group was characterized by an unfavorable immune microenvironment, marked by reduced levels of CD4 + T cells and natural killer cells, but increased M2 macrophages and regulatory T cells. Finally, the risk model was predictive of response to immune checkpoint blockade, as well as sensitivity to sunitinib and paclitaxel. The PANoptosis-related risk model developed in this study enables accurate prognostic prediction in KIRC patients. Its associations with the tumor immune microenvironment and drug efficacy may offer potential therapeutic targets and inform clinical decisions.

Cone-Traced Supersampling with Subpixel Edge Reconstruction.

While signed distance fields (SDFs) in theory offer infinite level of detail, they are typically rendered using the sphere tracing algorithm at finite resolutions, which causes the common rasterized image synthesis problem of aliasing. Most existing optimized antialiasing solutions rely on polygon mesh representations; SDF-based geometry can only be directly antialiased with the computationally expensive supersampling or with post-processing filters that may produce undesirable blurriness and ghosting. In this work, we present cone-traced supersampling (CTSS), an efficient and robust spatial antialiasing solution that naturally complements the sphere tracing algorithm, does not require casting additional rays per pixel or offline prefiltering, and can be easily implemented in existing real-time SDF renderers. CTSS performs supersampling along the traced ray near surfaces with partial visibility - object contours - identified by evaluating cone intersections within a pixel's view frustum. We further introduce subpixel edge reconstruction (SER), a technique that extends CTSS to locate and resolve complex pixels with geometric edges in relatively flat regions, which are otherwise undetected by cone intersections. Our combined solution relies on a specialized sampling strategy to minimize the number of shading computations and correlates sample visibility to aggregate the samples. With comparable antialiasing quality at significantly lower computational cost, CTSS is a reliable practical alternative to conventional supersampling.

[Effects of Tomato Planting Years on Soil Physical and Chemical Properties and Microbial Communities].

Long-term continuous cropping of facility soils could influence soil properties; however, the differences in soil properties among different continuous cropping years are still not well understood. The objective of this study was to explore the effects of continuous cropping years of tomato on the physical and chemical properties and biological characteristics of facility soil. Conventional analysis, high-throughput sequencing, and other methods were used to examine the soil physicochemical properties, soil microbial community diversity, and enzyme activities in facility soil after continuous tomato cropping for 1-3 years, 5-7 years, and more than 10 years. As the continuous tomato cropping years increased, soil bulk density and pH decreased; soil maximal water holding capacity increased; and organic matter, total nitrogen, and total phosphorus accumulated. As continuous cropping years increased, the total salt and EC value decreased with continuous cropping for 5-7 years and increased from 5-7 years to more than 10 years continuous cropping and showed a trend of secondary soil salinization. There was a significant increase in alkaline phosphatase for 1-3 years to 5-7 years continuous tomato cropping. There were significant differences in fungal community abundance among different cropping years. The Simpson index and Shannon index of fungi showed a trend of increasing first and then decreasing with the extension of continuous cropping years and reached the maximum value at 5 years of continuous cropping. The Chao1 index decreased continuously following the cropping years. As continuous cropping years increased, Streptomyces became the dominant bacteria, and Aspergillus and Pseudaleuria became the dominant fungi. The key factors affected by continuous cropping years were available potassium and available nitrogen based on the redundancy analysis. The results of this study lay the foundation for future research on the influence of continuous cropping years on the health of facility soil.

[Microbial Diversity and Population Structure of Different Salinized Soil Types in Hebei Province].

The objective of this study was to explore the microbial diversity and community composition under saline soil and to screen the salt-tolerant microbial flora from salinization habitats. The soil from three different habitats(primary salinization, secondary salinization, and healthy soil) in Hebei Province were sampled. The convention method and high-throughput sequencing technology were used to examine the physicochemical properties and microorganism diversity. The soil chemical properties of the three habitats were significantly different. Compared with those of field soil, the soil OM, AP, AK, TS, and EC values of greenhouse soil and TS and EC values of coastal saline soil were significantly higher. However, other chemical indexes of coastal saline soil were significantly lower. The diversity index and abundance of soil bacteria in greenhouse soil were the highest, followed by those in field soil and coastal saline soil as the lowest. The diversity index and abundance of fungi in two saline habitats were significantly lower than that in field soil. The community structure of saline soil was analyzed at the phylum and genus levels. Chloroflexi and its genera and Ascomycota and its genera, such as Trichocladium and Fusarium, were the dominant microbial groups in saline soil. EC and TS were the main factors affecting microbial diversity and community composition. EC and TS were positively correlated with unclassified_A4b, unclassified_Chloroflexi, unclassified_α-Proteobacteria, Trichocladium, unclassified_Chaetomiaceae, Crassicarpon, Cephaliophora, and Sodiomyces. The results of this study lay the foundation for future research on screening microbial resources needed for saline soil remediation.

Electrocatalytic Degradation of Rhodamine B on the Sb-Doped SnO2/Ti Electrode in Alkaline Medium.

To realize efficient electrocatalytic degradation of organic compounds in alkaline wastewater, an Sb-doped SnO2/Ti electrode was fabricated and employed for the removal of Rhodamine B (RhB), and the electrocatalytic oxidation performance of this electrode was assessed in an alkaline medium. In an alkaline solution (pH 11), the complete fading of 50 mg·L-1 RhB could be achieved after 150 min of degradation, the removal efficiency of the chemical oxygen demand reached 56.1% at 300 min, and the degradation process of RhB followed the pseudo-first-order kinetic model very well. Under the attack of hydroxyl radicals, partial RhB was degraded to low-molecular-weight organic acids through N-demethylation and the destruction of the conjugated chromophore. Various techniques including scanning electron microscopy, X-ray diffraction, X-ray photoelectron spectroscopy, and cycle voltammetry were used to examine the changes in the morphology and structure, as well as the activity of the Sb-doped SnO2/Ti electrode before and after use. The Sb-doped SnO2/Ti electrode could be reproduced in batches, and each electrode was reused up to eight times without a significant decrease in degradation ability; the leaching amount of antimony was significantly lower than the national emission standard. The electrocatalytic oxidation of the dye wastewater sample was also performed with the desired results, indicating that electrochemical oxidation is a very promising technology for the treatment of alkaline dye wastewater using a Sb-doped SnO2/Ti electrode.

The electronic and optical properties of Cs2BX6 (B = Zr, Hf) perovskites with first-principle method.

The electronic structures and absorption properties of Cs2BX6 halide compounds are investigated with first principle calculation and exchange correlation functional of GGA-PBE. Pressure and halogen ion doping are employed to regulate band gap. All materials suffer transition from indirect to direct band gap semiconductors but with different phase transition pressure. Structural and band structure calculating results show that the value of phase transition pressure is mainly determined by the volume of octahedron. When the volume of vacancy octahedron is much less than B-ion octahedron, the lowest band point of B-d orbitals transforms to Γ point, then the indirect semiconductors transform into direct band gap semiconductors. Calculating results of optical absorption implied that the systems have obvious blue shift, which result in the optical properties reduced. Based on suitable band gap and higher absorption coefficient, Cs2ZrI4Br2 can be an ideal candidate for perovskites solar cells.

Antifungal Compound from the Predatory Bacterium Lysobacter enzymogenes Inhibits a Plant Pathogenic Fungus by Targeting the AAA ATPase VpVeb1.

Heat-stable antifungal factor (HSAF) isolated from Lysobacter enzymogenes is considered a potential biocontrol agent. However, the target of HSAF in phytopathogenic fungi remains unclear. In this study, we investigated the target of HSAF in Valsa pyri that causes fatal pear Valsa canker. Thirty-one HSAF-binding proteins were captured and identified by surface plasmon resonance (SPR) and high-performance liquid chromatography-mass spectrometry (LC-MS/MS), and 11 deletion mutants were obtained. Among these mutants, only ΔVpVEB1 showed decreased sensitivity to HSAF. Additionally, ΔVpVEB1 exhibited significantly reduced virulence in V. pyri. Molecular docking and SPR results revealed that HSAF bound to threonine 569 and glycine 570 of VpVeb1, which are crucial for AAA ATPase activity. Another study showed that HSAF could decrease the ATPase activity of VpVeb1, leading to the reduced virulence of V. pyri. Taken together, this study first identified the potential target of HSAF in fungi. These findings will help us better understand the model of action of HSAF to fungi.

Structure-based virtual screening and fragment replacement to design novel inhibitors of Coxsackievirus A16 (CVA16).

Numerous studies have shown that hand, foot and mouth disease (HFMD) pathogen Coxsackievirus A16 (CVA16) can also cause severe neurological complications and even death. Currently, there is no effective drugs and vaccines for CVA16. Therefore, developing a drug against CVA16 has become critical. In this study, we conducted two strategies-virtual screening (VS) and fragment replacement to obtain better candidates than the known drug GPP3. Through VS, 37 candidate drugs were screened (exhibiting a lower binding energy than GPP3). After toxicity evaluations, we obtained five candidates, analysed their binding modes and found that four candidates could enter the binding pocket of the GPP3. In another strategy, we analysed the four positions in GPP3 structures by the FragRep webserver and obtained a large number of candidates after replacing different functional groups, we obtained eight candidates (that target the four positions above) with the combined binding score and synthetic accessibility evaluations. AMDock software was uniformly utilized to perform molecular docking evaluation of the candidates with binding activity superior to that of GPP3. Finally, the selected top three molecules (Lapatinib, B001 and C001) and its interaction with CAV16 were validated by molecular dynamics (MD) simulation. The results indicated that all three molecules retain inside the pocket of CAV16 receptor throughout the simulation process, and he binding energy calculated from the MD simulation trajectories also support the strong affinity of the top three molecules towards the CVA16. These results will provide new ideas and technical guidance for designing and applying CVA16 therapeutics.Communicated by Ramaswamy H. Sarma.

HIGHLIGHTSThe dual strategies of computer-aided VS and fragment replacement were first used to obtain candidate small molecules with stronger binding activity than the hand-foot-mouth COV16 viral drug molecule GPP3.The binding patterns of GPP3 and several candidate molecules obtained by VS were analyzed, and a new and interesting binding pattern was found ­ binding at the entrance of the pocket instead of inside the pocket.The Top3 candidate molecules were verified by MD simulations.Through molecular docking, a comprehensive comparative analysis was conducted between all candidate molecules obtained in this study and anti-hand-foot-mouth virus drugs used in clinic.

Engineered rare-earth nanomaterials for fluorescence imaging and therapy.

Early diagnosis and treatment are of great significance for hindering the progression of brain disease. The limited effects of available treatments and poor prognosis are currently the most pressing problems faced by clinicians and their patients. Therefore, developing new diagnosis and treatment programs for brain diseases is urgently needed. Near-infrared (NIR)-light-responsive, lanthanide-doped upconversion nanoparticles (UCNPs) provide great advantages both in diagnosis and therapy. Hence, we synthesised nanoparticles comprised of a UCNPs core with surface functionalization. UCNPs@Au was used for NIR fluorescence imaging in the brain and inhibiting the growth of mouse glioma 261 (GL261) cells depending on photothermal properties. In addition, a UCNPs core and a mesoporous silica layer as the outer shell with a tannic acid-Al3+ ions (TA-Al) complex as a "gatekeeper" were used for pH-triggered doxorubicin/small interfering ribonucleic acid delivery in vitro. Based on our preliminary results, we expect to develop more multifunctional nanoscale diagnostic and therapeutic agents based on UCNPs for the diagnosis and treatment of brain diseases, including Alzheimer's disease, Parkinson's disease, and brain tumours.

A deep learning method for foot-type classification using plantar pressure images.

Background: Flat foot deformity is a prevalent and challenging condition often leading to various clinical complications. Accurate identification of abnormal foot types is essential for appropriate interventions. Method: A dataset consisting of 1573 plantar pressure images from 125 individuals was collected. The performance of the You Only Look Once v5 (YOLO-v5) model, improved YOLO-v5 model, and multi-label classification model was evaluated for foot type identification using the collected images. A new dataset was also collected to verify and compare the models. Results: The multi-label classification algorithm based on ResNet-50 outperformed other algorithms. The improved YOLO-v5 model with Squeeze-and-Excitation (SE), the improved YOLO-v5 model with Convolutional Block Attention Module (CBAM), and the multilabel classification model based on ResNet-50 achieved an accuracy of 0.652, 0.717, and 0.826, respectively, which is significantly higher than those obtained using the ordinary plantar-pressure system and the standard YOLO-v5 model. Conclusion: These results indicate that the proposed DL-based multilabel classification model based on ResNet-50 is superior in flat foot type detection and can be used to evaluate the clinical rehabilitation status of patients with abnormal foot types and various foot pathologies when more data on patients with various diseases are available for training.