[Retracted] RNAi­mediated EZH2 depletion decreases MDR1 expression and sensitizes multidrug­resistant hepatocellular carcinoma cells to chemotherapy.

Following the publication of this paper, it was drawn to the Editor's attention by a concerned reader that the control western blotting data featured in Fig. 2C on p. 1039 and the cell cycle distribution images shown in Fig. 6A on p. 1041 were strikingly similar to data that had appeared in a pair of other articles written by different authors at different research institutes, one of which had already been submitted for publication when this article was received at Oncology Reports, the other of which was received some time afterwards, but which has subsequently been retracted. Owing to the fact that the abovementioned data had already been submitted for publication prior to its submission to Oncology Reports, the Editor has decided that this paper should be retracted from the Journal. The authors were asked for an explanation to account for these concerns, but the Editorial Office did not receive a reply. The Editor apologizes to the readership for any inconvenience caused. [Oncology Reports 29: 1037­1042, 2013; DOI: 10.3892/or.2013.2222].

The COL7A1/PI3K/AKT axis regulates the progression of cholangiocarcinoma.

Background: The role and molecular mechanisms of collagen type VII (COL7A1) in cholangiocarcinoma (CCA) remain unknown. Methods: We analyzed the expression of COL7A1 in CCA and its relationship with patient prognosis using bioinformatic techniques. Expression levels of COL7A1 in CCA cells and tissues were detected using reverse transcription-quantitative PCR, western blotting, and immunohistochemistry. The effects of COL7A1 expression on the proliferation, migration, and invasion of CCA cells were assessed using CCK-8, colony formation, and Transwell assays. Bioinformatics and luciferase reporter gene assays were performed to examine the binding of KLF4 to COL7A1, and cytological experiments further verified the role of KLF4 in regulating the CCA phenotype through COL7A1. Xenograft mouse models were established to investigate the effects of COL7A1 on CCA tumor growth in vivo. Results: CCA tissues exhibited higher COL7A1 expression than normal bile duct tissues. There was no significant correlation between high or low COL7A1 expression and the survival time of patients with CCA. COL7A1 knockdown inhibited CCA cell proliferation, migration, and invasion. Furthermore, COL7A1 knockdown suppressed the activation of the PI3K/AKT signaling pathway. KLF4 can bind to COL7A1 and regulate COL7A1 expression, which in turn regulates the PI3K/AKT signaling pathway and impacts the proliferation and metastasis of CCA cells. Conclusion: Our findings suggest that KLF4 regulates CCA cell proliferation, migration, and invasion via the COL7A1/PI3K/AKT axis.

Evaluation of Multigene Methylation for Blood-Based Detection of Colorectal Cancer.

Background: Early screening for colorectal cancer (CRC) has the potential to improve patient prognosis, but current screening methods are limited. In this prospective study, we aimed to evaluate the multigene (Septin9, SDC2, KCNQ5, and IKZF1) detection in patient plasma for CRC diagnosis. Methods: Overall, 67 participants were enrolled, including 31 patients with CRC, 17 patients with colorectal polyp, and 19 normal controls who underwent colonoscopy. Carcinoembryonic antigen (CEA) and Septin9, SDC2, KCNQ5, and IKZF1 methylation tests were performed. Sensitivity, specificity, and the area under the receiver operating characteristic (ROC) curve were used to evaluate the diagnostic value of each biomarker. The association between positive rates of methylated Septin9, SDC2, KCNQ5, and IKZF1 and the clinicopathological characteristics of CRC was also analyzed. Results: The positive rate of multigene methylation detection was 87.1% (27/31) in patients with CRC, which was higher than single indicators: CEA (51.61%, 16/31), Septin9 (41.94%, 13/31), SDC2 (41.94%, 13/31), KCNQ5 (58.06%, 18/31), and IKZF1 (32.26%, 10/31). In the colorectal polyp group, the rate of multigene methylation detection is 88.24% (15/17), which was also higher than single indicator: CEA (17.65%, 3/17), Septin9 (11.76%, 2/17), SDC2 (64.71%, 11/17), KCNQ5 (58.82%, 10/17), and IKZF1 (35.29%, 6/17). The ROC curves further showed better diagnostic value of the multigene test for CRC than any single gene. Correlation analysis found that the positive rate of the test was not affected by patients' clinicopathologic characteristics. Conclusion: The combination of methylated Septin9, SDC2, KCNQ5, and IKZF1 tests is preferable to individual gene tests for patients with CRC and polyp.

A machine learning-based crashworthiness optimization for a novel pine cone-inspired multi-cell tubes under bending.

Bionic tubes are of interest in vehicle engineering due to their superior crashworthiness potential. This study proposes a crashworthiness response investigation and machine learning-based multi-objective optimization of pine cone-inspired muti-celled tubes (PCMTs). The base computer PCMT model was correlated using existing experiments, followed by a dynamic response evaluation of different PCMT geometrical and thickness configurations to assess their structural performance. Surrogate models of these PCMTs were then constructed using machine learning algorithms, and their main and interaction effects were analyzed. A non-dominated sorting genetic algorithm II (NSGA-II) approach was employed to perform a multi-objective optimization. The results demonstrate that thickness change had more effect on the initial peak force (IPF) and the mean crushing force (MCF) than the specific energy absorption (SEA). Besides, due to the coupling effect, IPF, MCF and SEA of the optimal design solution of the PCMTs could reach a 36.82 %, 61.66 % and 72.95 % increase than the sum case, suggesting that embedding inner tubes could significantly increase energy absorption with a relative minor IPF increase. Moreover, the MCF and SEA of optimal design gave an average difference of 18.01 % and 5.91 % from the original tubes. PCMTs, therefore, could be used as an ideal energy absorption structure in the vehicle body structures.

Creatinine-to-cystatin C ratio and frailty in older adults: a longitudinal cohort study.

BACKGROUND: Creatinine-to-cystatin C ratio (CCR) has been associated with multiple adverse outcomes. However, little is known about its relationship with frailty. We aimed to explore the association between CCR and frailty among older adults. METHODS: A total of 2599 participants aged ≥ 60 years (mean age 67.9 ± 6.0 years, 50.4% males) were included from the China Health and Retirement Longitudinal Study (2011-2015). Baseline CCR was calculated as plasma creatinine (mg/dL) / cystatin C (mg/L) × 10 and was grouped by quartiles. Frailty was evaluated by the validated physical frailty phenotype (PFP) scale and was defined as PFP score ≥ 3. The generalized estimating equations model was used to explore the relationship between CCR and frailty. RESULTS: The frailty risk decreased gradually with increasing CCR in the quartiles (P for trend = 0.002), and the fourth CCR quartile was associated with a significantly lower risk of frailty compared with the lowest quartile (odds ratio [OR] 0.37, 95% confidence interval [CI] 0.19-0.70). When modeling as a continuous variable, per 1-unit increase in CCR was related to 17% decreased odds of frailty (OR 0.83, 95% CI 0.74-0.93). The association was consistent in male and female participants (P for interaction = 0.41). Poisson models revealed that frailty score was negatively associated with CCR (ß= -0.11, 95% CI= -0.19 to -0.04), and sex did not significantly moderate the associations (P for interaction = 0.22). The results were not affected by further adjusting for high-sensitivity C-reactive protein. Similar results were observed by analyses with multiple imputation technique and analyses excluding participants with baseline frailty. CONCLUSIONS: Higher CCR was associated with a lower frailty risk. CCR may be a simple marker for predicting frailty in older adults.

Identification of novel broad-spectrum antiviral drugs targeting the N-terminal domain of the FIPV nucleocapsid protein.

Coronaviruses pose serious threats to human and animal health worldwide, of which their structural nucleocapsid (N) proteins play multiple key roles in viral replication. However, the structures of animal coronavirus N proteins are poorly understood, posing challenges for research on their functions and pathogenic mechanisms as well as the development of N protein-based antiviral drugs. Therefore, N proteins must be further explored as potential antiviral targets. We determined the structure of the NNTD of feline infectious peritonitis virus (FIPV) and identified 3,6-dihydroxyflavone (3,6- DHF) as an effective N protein inhibitor. 3,6-DHF successfully inhibited FIPV replication in CRFK cells, showing broad-spectrum activity and effectiveness against drugresistant strains. Our study provides important insights for developing novel broadspectrum anti-coronavirus drugs and treating infections caused by drug-resistant mutant strains.

Development and validation of a predictive model for end-stage renal disease in systemic lupus erythematosus patients.

Systemic lupus erythematosus (SLE) affects many populations. This study aims to develop a predictive model and create a nomogram for assessing the risk of end-stage renal disease (ESRD) in patients diagnosed with SLE. Data from electronic health records of SLE patients treated at the Affiliated Hospital of North Sichuan Medical College between 2013 and 2023 were collected. The dataset underwent thorough cleaning and variable assignment procedures. Subsequently, variables were selected using one-way logistic regression and lasso logistic regression methods, followed by multifactorial logistic regression to construct nomograms. The model's performance was assessed using calibration, receiver operating characteristic (ROC), and decision curve analysis (DCA) curves. Statistical significance was set at P < 0.05. The predictive variables for ESRD development in SLE patients included anti-GP210 antibody presence, urinary occult blood, proteinuria, white blood cell count, complement 4 levels, uric acid, creatinine, total protein, globulin, glomerular filtration rate, pH, specific gravity, very low-density lipoprotein, homocysteine, apolipoprotein B, and absolute counts of cytotoxic T cells. The nomogram exhibited a broad predictive range. The ROC area under the curve (AUC) was 0.886 (0.858-0.913) for the training set and 0.840 (0.783-0.897) for the testing set, indicating good model performance. The model demonstrated both applicability and significant clinical benefits. The developed model presents strong predictive capabilities and considerable clinical utility in estimating the risk of ESRD in patients with SLE.

Preparation and evaluation of a 1,1'-bi-2-naphthol-based chiral macrocycle bonded silica chiral stationary phase for high performance liquid chromatography.

Macrocycles play vital roles in supramolecular chemistry and chromatography. 1,1'-Bi-2-naphthol (BINOL)-based chiral polyimine macrocycles are an emerging class of chiral macrocycles that can be constructed by one-step aldehyde-amine condensation of BINOL derivatives with other building blocks. These macrocycles exhibit good characteristics, such as facile preparation, rigid cyclic structures, multiple chiral centers, and defined molecular cavities, that make them good candidates as new chiral recognition materials for chromatographic enantioseparations. In this study, a BINOL-based [2+2] chiral polyimine macrocycle was synthesized by one-step condensation of enantiopure (S)-2,2'-dihydroxy-[1,1'-binaphthalene]-3,3'-dicarboxaldehyde with (1R,2R)-1,2-diaminocyclohexane. The product was modified with 5-bromo-1-pentene and then attached to thiolated silica using click chemistry to construct a new chiral stationary phase (CSP). The enantioselectivity of the new CSP was explored by separating various racemates under normal phase (NP) and reversed phase (RP) high performance liquid chromatography (HPLC). Thirteen racemates and eight racemates were enantioseparated under the two separation modes, respectively, including chiral alcohols, phenols, esters, ketones, amines, and organic acids. Among them, nine racemates achieved baseline separation under NP-HPLC and seven racemates achieved baseline separation under RP-HPLC. High resolution separation was observed with benzoin (Rs = 5.10), epinephrine (Rs = 4.98), 3-benzyloxy-1,2-propanediol (Rs = 4.42), and 4,4'-dimethylbenzoin (Rs = 4.52) in NP-HPLC, and with 4-methylbenzhydrol (Rs = 4.72), benzoin ethyl ether (Rs = 3.79), 1-phenyl-1-pentanol (Rs = 3.68), and 1-(3-bromophenyl)ethanol (Rs = 3.60) in RP-HPLC. Interestingly, the CSP complemented Chiralcel OD-H, Chiralpak AD-H, and CYCLOBOND I 2000 RSP columns for resolution of these test racemates, separating several racemic compounds that could not be well separated by the three commercially available columns. The influences of injected sample amount on separation were also evaluated. It was found that the column exhibited excellent stability and reproducibility after hundreds of injections, and the relative standard deviations (n = 5) of the retention time and resolution were less than 0.49% and 0.69%, respectively. This study indicates that the BINOL-based chiral macrocycle has great potential for HPLC enantioseparation.

Calcitriol alleviates noise-induced hearing loss by regulating the ATF3/DUSP1 signalling pathway.

BACKGROUND: Calcitriol (Cal) is the most active metabolite of vitamin D and has antioxidant and anti-inflammatory properties. The aim of this study was to investigate the role of Cal in noise-induced hearing loss (NIHL) to further elucidate the mechanism of noise-induced oxidative stress in the mouse cochlea. METHODS: C57BL/6 J mice were given six intraperitoneal injections of Cal (500 ng/kg/d). After 14 days of noise exposure, auditory brainstem response (ABR) thresholds, and the cochlear outer hair cell loss rate were analysed to evaluate auditory function. Real-time fluorescence quantitative PCR, immunofluorescence and western blotting were performed in vitro after the treatment of cochlear explants with 100 µM tert-butyl hydroperoxide (TBHP) for 2.5 h and HEI-OC1 cells with 250 µM TBHP for 1.5 h. RESULTS: In vivo experiments confirmed that Cal pretreatment mitigated NIHL and outer hair cell death. The in vitro results demonstrated that Cal significantly reduced TBHP-induced cochlear auditory nerve fibre degradation and spiral ganglion neuron damage. Moreover, treatment with Cal inhibited the expression of oxidative stress-related factors (3-NT and 4-HNE) and DNA damage-related factors (γ-H2A.X) and attenuated TBHP-induced apoptosis in cochlear explants and HEI-OC1 cells. A total of 1479 upregulated genes and 1443 downregulated genes were screened in cochlear tissue 1 h after noise exposure. The level of transcription factor 3 (ATF3) was significantly elevated in HEI-OC1 cells after TBHP stimulation. Gene Transcription Regulation Database （GTRD）and Cistrome database analyses revealed that the downstream target gene of ATF3 is dual specificity phosphatase 1 (DUSP1). Cistrome DB Toolkit database results showed that the transcription factor of DUSP1 was ATF3. In addition, the ChIP-PCR results indicated that ATF3 might be a direct transcription factor of DUSP1. CONCLUSION: The results of our study suggest that Cal attenuates NIHL and inhibits noise-induced apoptosis by regulating the ATF3/DUSP1 signalling pathway.

Numerical and Experiment Analysis of Sapphire Sandwich-Structure Fabry-Perot Pressure Sensor through Fast Fourier Transform and Mean Square Error Demodulation Algorithm.

Pressure sensors prepared from sapphire exhibit excellent characteristics, including high-temperature resistance, high hardness, and resistance to electromagnetic interference. A Fast Fourier Transform and Mean Square Error (FFT-MSE) demodulation algorithm was employed to demodulate a sapphire sandwich-structure Fabry-Perot (F-P) pressure sensor. Through simulation analysis, the experimental results indicated that the demodulation error of the air cavity length in the range of 206 µm to 216 µm was less than 0.0008%. Compared to single demodulation methods and combined demodulation methods based on FFT or Minimum Mean Square Error (MMSE), the method proposed in this work reduced the demodulation error by more than three times and increased accuracy by more than six times. The algorithm was utilized to demodulate the sapphire sandwich-structure F-P pressure sensor, and the test results indicated that the fitting error of the sensor was less than 0.025% within the pressure range of 0 MPa to 10 MPa. The repeatability error was less than 0.066%, the zero-point deviation was 1.26%, and the maximum stability deviation was 0.0063% per 30 min. The algorithm effectively demodulated the actual cavity length variation in the sapphire sandwich-structure F-P pressure sensor, providing a solution for the performance evaluation of the sapphire sandwich-structure F-P pressure sensor.

Hypervirulent and carbapenem-resistant Klebsiella pneumoniae: A global public health threat.

The evolution of hypervirulent and carbapenem-resistant Klebsiella pneumoniae can be categorized into three main patterns: the evolution of KL1/KL2-hvKp strains into CR-hvKp, the evolution of carbapenem-resistant K. pneumoniae (CRKp) strains into hv-CRKp, and the acquisition of hybrid plasmids carrying carbapenem resistance and virulence genes by classical K. pneumoniae (cKp). These strains are characterized by multi-drug resistance, high virulence, and high infectivity. Currently, there are no effective methods for treating and surveillance this pathogen. In addition, the continuous horizontal transfer and clonal spread of these bacteria under the pressure of hospital antibiotics have led to the emergence of more drug-resistant strains. This review discusses the evolution and distribution characteristics of hypervirulent and carbapenem-resistant K. pneumoniae, the mechanisms of carbapenem resistance and hypervirulence, risk factors for susceptibility, infection syndromes, treatment regimens, real-time surveillance and preventive control measures. It also outlines the resistance mechanisms of antimicrobial drugs used to treat this pathogen, providing insights for developing new drugs, combination therapies, and a "One Health" approach. Narrowing the scope of surveillance but intensifying implementation efforts is a viable solution. Monitoring of strains can be focused primarily on hospitals and urban wastewater treatment plants.

Performance Study of F-P Pressure Sensor Based on Three-Wavelength Demodulation: High-Temperature, High-Pressure, and High-Dynamic Measurements.

F-P (Fabry-Perot) pressure sensors have a wide range of potential applications in high-temperature, high-pressure, and high-dynamic environments. However, existing demodulation methods commonly rely on spectrometers, which limits their application to high-frequency pressure signal acquisition. To solve this problem, this study developed a self-compensated, three-wavelength demodulation system composite with an F-P pressure sensor and a thermocouple to construct a comprehensive sensing system. The system produces accurate pressure measurements in high-temperature, high-pressure, and high-dynamic environments. In static testing at room temperature, the sensing system shows excellent linearity, and the pressure sensitivity is 158.48 nm/MPa. In high-temperature testing, the sensing system maintains high linearity in the range of 100 °C to 700 °C, with a maximum pressure-indication error of about 0.13 MPa (0~5 MPa). In dynamic testing, the sensor exhibits good response characteristics at 1000 Hz and 5000 Hz sinusoidal pressure frequencies, with a signal-to-noise ratio (SNR) greater than 37 dB and 45 dB, respectively. These results indicate that the sensing system proposed in this study has significant competitive advantages in the field of high-temperature, high-speed, and high-precision pressure measurements and provides an important experimental basis and theoretical support for technological progress in related fields.

Evaluation of the proportional hazards assumption and covariate adjustment methods in comparative surgical observational studies with time-to-event endpoints.

INTRODUCTION: Comparative studies on surgical treatments with time-to-event endpoints have provided substantial evidence for clinical practice, but the accurate use of survival data analysis and the control of confounding bias remain big challenges. METHODS: This was a survey of surgical studies with survival outcomes published in four general medical journals and five general surgical journals in 2021. The two most concerned statistical issues were evaluated, including confounding control by propensity score analysis (PSA) or multivariable analysis and testing of proportional hazards (PH) assumption in Cox model. RESULTS: A total of 74 studies were included, comprising 63 observational studies and 11 randomized controlled trials. Among the observational studies, the proportion of studies utilizing PSA in surgical oncology and non-oncology studies was similar (40.9 % versus 36.8 %, P = 0.762). However, the former reported a significantly lower proportion of PH assumption assessments compared to the latter (13.6 % versus 42.1 %, P = 0.020). Twenty-five observational studies (25/63) used PSA methods, but two-thirds of them (17/25) showed unclear balance of baseline data after PSA. And the proportion of PH assumption testing after PSA was slightly lower than that before PSA, but the difference was not statistically significant (24.0 % versus 28.0 %, P = 0.317). Comprehensive suggestions were given on confounding control in survival analysis and alternative resolutions for non-compliance with PH assumption. CONCLUSION: This study highlights suboptimal reporting of PH assumption evaluation in observational surgical studies both before and after PSA. Efforts and consensus are needed with respect to the underlying assumptions of statistical methods.

The miR-203/ZBTB20/MAFA Axis Orchestrates Pancreatic ß-Cell Maturation and Identity During Weaning and Diabetes.

Maturation of postnatal ß-cells is regulated in a cell-autonomous manner, and metabolically stressed ß-cells regress to an immature state, ensuring defective ß-cell function and the onset of type 2 diabetes. The molecular mechanisms connecting the nutritional transition to ß-cell maturation remain largely unknown. Here, we report a mature form of miRNA (miR-203)/ZBTB20/MAFA regulatory axis that mediates the ß-cell maturation process. We show that the level of the mature form of miRNA (miR-203) in ß-cells changes during the nutritional transition and that miR-203 inhibits ß-cell maturation at the neonatal stage and under high-fat diet conditions. Using single-cell RNA sequencing, we demonstrated that miR-203 elevation promoted the transition of immature ß-cells into CgBHi endocrine cells while suppressing gene expressions associated with ß-cell maturation in a ZBTB20/MAFA-dependent manner. ZBTB20 is an authentic target of miR-203 and transcriptionally upregulates MAFA expression. Manipulating the miR-203/ZBTB20/MAFA axis may therefore offer a novel strategy for boosting functional ß-cell numbers to alleviate diabetes.

A WKNN Indoor Fingerprint Localization Technique Based on Improved Discrimination Capability of RSS Similarity.

There are various indoor fingerprint localization techniques utilizing the similarity of received signal strength (RSS) to discriminate the similarity of positions. However, due to the varied states of different wireless access points (APs), each AP's contribution to RSS similarity varies, which affects the accuracy of localization. In our study, we analyzed several critical causes that affect APs' contribution, including APs' health states and APs' positions. Inspired by these insights, for a large-scale indoor space with ubiquitous APs, a threshold was set for all sample RSS to eliminate the abnormal APs dynamically, a correction quantity for each RSS was provided by the distance between the AP and the sample position to emphasize closer APs, and a priority weight was designed by RSS differences (RSSD) to further optimize the capability of fingerprint distances (FDs, the Euclidean distance of RSS) to discriminate physical distance (PDs, the Euclidean distance of positions). Integrating the above policies for the classical WKNN algorithm, a new indoor fingerprint localization technique is redefined, referred to as FDs' discrimination capability improvement WKNN (FDDC-WKNN). Our simulation results showed that the correlation and consistency between FDs and PDs are well improved, with the strong correlation increasing from 0 to 76% and the high consistency increasing from 26% to 99%, which confirms that the proposed policies can greatly enhance the discrimination capabilities of RSS similarity. We also found that abnormal APs can cause significant impact on FDs discrimination capability. Further, by implementing the FDDC-WKNN algorithm in experiments, we obtained the optimal K value in both the simulation scene and real library scene, under which the mean errors have been reduced from 2.2732 m to 1.2290 m and from 4.0489 m to 2.4320 m, respectively. In addition, compared to not using the FDDC-WKNN, the cumulative distribution function (CDF) of the localization errors curve converged faster and the error fluctuation was smaller, which demonstrates the FDDC-WKNN having stronger robustness and more stable localization performance.

Amplifying Chinese physicians' emphasis on patients' psychological states beyond urologic diagnoses with ChatGPT-A multi-center cross-sectional study.

BACKGROUND: Artificial intelligence (AI) technologies, particularly large language models (LLMs), have been widely employed by the medical community. In addressing the intricacies of urology, ChatGPT offers a novel possibility to aid in clinical decision-making. This study aimed to investigate the decision-making ability of LLMs in solving complex urology-related problems and assess its effectiveness in providing psychological support to patients with urological disorders. MATERIALS AND METHODS: This study evaluated the clinical and psychological support capabilities of ChatGPT 3.5 and 4.0 in the field of urology. A total of 69 clinical and 30 psychological questions were posed to the AI models, and their responses were evaluated by both urologists and psychologists. As a control, clinicians from Chinese medical institutions provided responses under closed-book conditions. Statistical analyses were conducted separately for each subgroup. RESULTS: In multiple-choice tests covering diverse urological topics, ChatGPT 4.0, performed comparably to the physician group, with no significant overall score difference. Subgroup analyses revealed variable performance, based on disease type and physician experience, with ChatGPT 4.0 generally outperforming ChatGPT 3.5 and exhibiting competitive results against physicians. When assessing the psychological support capabilities of AI, it is evident that ChatGPT4.0 outperforms ChatGPT3.5 across all urology-related psychological problems. CONCLUSIONS: The performance of LLMs in dealing with standardized clinical problems and providing psychological support has certain advantages over clinicians. AI stands out as a promising tool for potential clinical aid.

Sharing massive biomedical data at magnitudes lower bandwidth using implicit neural function.

Efficient storage and sharing of massive biomedical data would open up their wide accessibility to different institutions and disciplines. However, compressors tailored for natural photos/videos are rapidly limited for biomedical data, while emerging deep learning-based methods demand huge training data and are difficult to generalize. Here, we propose to conduct Biomedical data compRession with Implicit nEural Function (BRIEF) by representing the target data with compact neural networks, which are data specific and thus have no generalization issues. Benefiting from the strong representation capability of implicit neural function, BRIEF achieves 2[Formula: see text]3 orders of magnitude compression on diverse biomedical data at significantly higher fidelity than existing techniques. Besides, BRIEF is of consistent performance across the whole data volume, and supports customized spatially varying fidelity. BRIEF's multifold advantageous features also serve reliable downstream tasks at low bandwidth. Our approach will facilitate low-bandwidth data sharing and promote collaboration and progress in the biomedical field.

The combination of modified acupuncture needle and melittin hydrogel as a novel therapeutic approach for rheumatoid arthritis treatment.

Rheumatoid arthritis (RA) involves chronic joint inflammation. Combining acupuncture and medication for RA treatment faces challenges like spatiotemporal variability, limited drug loading in acupuncture needles, and premature or untargeted drug release. Here, we designed a new type of tubular acupuncture needles, with an etched hollow honeycomb-like structure to enable the high loading of therapeutics, integrating the traditional acupuncture and drug repository into an all-in-one therapeutic platform. In these proof-of-concept experiments, we fabricated injectable hollow honeycomb electroacupuncture needles (HC-EA) loaded with melittin hydrogel (MLT-Gel), enabling the combination treatment of acupuncture stimulation and melittin therapy in a spatiotemporally synchronous manner. Since the RA microenvironment is mildly acidic, the acid-responsive chitosan (CS)/sodium beta-glycerophosphate (ß-GP)/ hyaluronic acid (HA) composited hydrogel (CS/GP/HA) was utilized to perform acupuncture stimulation and achieve the targeted release of injected therapeutics into the specific lesion site. Testing our therapeutic platform involved a mouse model of RA and bioinformatics analysis. MLT-Gel@HC-EA treatment restored Th17/Treg-mediated immunity balance, reduced inflammatory factor release (TNF-α, IL-6, IL-1ß), and alleviated inflammation at the lesion site. This novel combination of modified acupuncture needle and medication, specifically melittin hydrogel, holds promise as a therapeutic strategy for RA treatment.

Development and validation of a COVID-19 vaccination prediction model based on self-reporting results in Chinese older adults from September 2022 to November 2022: A nationwide cross-sectional study.

It was common to see that older adults were reluctant to be vaccinated for coronavirus disease 2019 (COVID-19) in China. There is a lack of practical prediction models to guide COVID-19 vaccination program. A nationwide, self-reported, cross-sectional survey was conducted from September 2022 to November 2022, including people aged 60 years or older. Stratified random sampling was used to divide the dataset into derivation, validation, and test datasets at a ratio of 6:2:2. Least absolute shrinkage and selection operator and multivariable logistic regression were used for variable screening and model construction. Discrimination and calibration were assessed primarily by area under the receiver operating characteristic curve (AUC) and calibration curve. A total of 35057 samples (53.65% males and mean age of 69.64 ± 7.24 years) were finally selected, which constitutes 93.73% of the valid samples. From 33 potential predictors, 19 variables were screened and included in the multivariable logistic regression model. The mean AUC in the validation dataset was 0.802, with sensitivity, specificity, and accuracy of 0.732, 0.718 and 0.729 respectively, which were similar to the parameters in the test dataset of 0.755, 0.715 and 0.720, respectively, and the mean AUC in the test dataset was 0.815. There were no significant differences between the model predicted values and the actual observed values for calibration in these groups. The prediction model based on self-reported characteristics of older adults was developed that could be useful for predicting the willingness for COVID-19 vaccines, as well as providing recommendations in improving vaccine acceptance.