PCSK9 inhibitors and osteoporosis: mendelian randomization and meta-analysis.

BACKGROUND: Proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors represent an effective strategy for reducing cardiovascular disease risk. Yet, PCSK9's impact on osteoporosis remains unclear. Hence, we employed Mendelian randomization (MR) analysis for examining PCSK9 inhibitor effects on osteoporosis. METHODS: Single nucleotide polymorphisms (SNPs) for 3-hydroxy-3-methylglutaryl cofactor A reductase (HMGCR) and PCSK9 were gathered from available online databases for European pedigrees. Four osteoporosis-related genome-wide association studies (GWAS) data served as the main outcomes, and coronary artery disease (CAD) as a positive control for drug-targeted MR analyses. The results of MR analyses examined by sensitivity analyses were incorporated into a meta-analysis for examining causality between PCSK9 and HMGCR inhibitors and osteoporosis. RESULTS: The meta-analysis involving a total of 1,263,102 subjects, showed that PCSK9 inhibitors can increase osteoporosis risk (P < 0.05, I2, 39%). However, HMGCR inhibitors are not associated with osteoporosis risk. Additionally, a replication of the analysis was conducted with another exposure-related GWAS dataset, which led to similar conclusions. CONCLUSION: PCSK9 inhibitors increase osteoporosis risk. However, HMGCR inhibitors are unremarkably linked to osteoporosis.

Construction and Validation of a Risk Prediction Model for Mild Cognitive Impairment in Non-Dialysis Chronic Kidney Disease Patient.

INTRODUCTION: To explore the factors affecting mild cognitive impairment in patients with chronic kidney disease who are not undergoing dialysis, and to construct and validate a nomogram risk prediction model. METHODS: Using a convenience sampling method, 383 non-dialysis chronic kidney disease (CKD) patients from two tertiary hospitals in Chengdu were selected between February 2023 and August 2023 to form the modeling group. The patients were divided into a mild cognitive impairment group (n=192) and a non-mild cognitive impairment group (n=191), and factors such as demographics, disease data, and sleep disorders were compared between the two groups. Univariate and multivariate binary logistic regression analyses were used to identify independent influencing factors, followed by collinearity testing, and construction of the regression model. The final risk prediction model was presented through a nomogram and an online calculator, with internal validation using Bootstrap sampling. For external validation, 137 non-dialysis CKD patients from another tertiary hospital in Chengdu were selected between October 2023 and December 2023. RESULTS: In the modeling group, 192 (50.1%) of the non-dialysis CKD patients developed mild cognitive impairment, and in the validation group, 56 (40.9%) patients developed mild cognitive impairment, totaling 248 (47.7%) of all sampled non-dialysis CKD patients. Age, educational level, Occupation status, Use of smartphone, sleep disorders, hemoglobin, and platelet count were independent factors influencing the occurrence of mild cognitive impairment in non-dialysis CKD patients (all P<0.05). The model evaluation showed an area under the ROC curve of 0.928, 95%CI (0.902, 0.953) in the modeling group, and 0.897, 95%CI (0.844, 0.950) in the validation group. The model's Youden index was 0.707, with an optimal cutoff value of 0.494, sensitivity of 0.853, and specificity of 0.854, indicating good predictive performance; calibration curves, Hosmer-Lemeshow test, and clinical decision curves indicated good calibration and clinical benefit. Internal validation results showed a consistency index (C-index) of 0.928, 95%CI (0.902, 0.953). CONCLUSION: The risk prediction model developed in this study shows excellent performance, demonstrating significant predictive potential for early screening of mild cognitive impairment in non-dialysis chronic kidney disease patients. The application of this model will provide a reference for healthcare professionals, helping them formulate more targeted intervention strategies to optimize patient treatment and management outcomes.

Global prevalence of obesity in patients with psoriasis: An analysis in the past two decades.

BACKGROUND: Psoriasis and obesity are risk factors for psoriasis. Therefore, we conducted a comprehensive review and meta-analysis to determine the prevalence of obesity in patients with psoriasis. METHODS: We examined four databases from their inception to October 2023 and used the Agency for Healthcare Research and Quality and the Newcastle-Ottawa Scale to assess the quality of observational studies. Data analysis was conducted using R language. Meta-regression, sensitivity and subgroup analyses were used to evaluate inter-study heterogeneity. Egger's test and funnel plots were used to evaluate publication bias. RESULTS: The global prevalence of psoriasis and obesity comorbidity was 25% (95% confidence interval [CI]: 0.21-0.30). Furthermore, the co-morbidity rate was 18% (95% CI: 0.11-0.24) in children and adolescents, and 35% (95% CI: 0.30-0.39) in adults. The gender-specific prevalence rates were 23% (95% CI: 0.16-0.32) in men and 38% (95% CI: 0.20-0.61) in women. Africa had the highest prevalence (60%, 95% CI: 0.21-0.99), followed by Asia (40%, 95% CI: 0.28-0.51), while Europe and North America had similar prevalence rates at 34% (95% CI: 0.27-0.41) and 31% (95% CI: 0.27-0.38), respectively. Regarding psoriasis severity, obesity was higher in moderate psoriasis (36%, 95% CI: 0.20-0.64) and lower in mild psoriasis (27%, 95% CI: 0.16-0.46). The prevalence of severe psoriasis was 30% (95% CI: 0.20-0.45). CONCLUSION: This study underscores the importance of identifying and treating obesity in patients with psoriasis to mitigate disease progression. However, more high-quality observational studies are required to elucidate their global prevalence and comorbid associations.

The association between osteoporosis and frailty: a cross-sectional observational study and mendelian randomization analysis.

BACKGROUND: Osteoporosis and frailty are two common features in the elderly population. Despite many review articles mentioning the association between osteoporosis and frailty, there is a lack of original research directly investigating their relationship. Therefore, this study was conducted to examine the correlation between osteoporosis and frailty. METHODS: We conducted a cross-sectional study using data from the National Health and Nutrition Examination Survey (NHANES), using logistic regression analysis to assess the association of osteoporosis with the frailty index. In addition, we further explored the causal relationship between them using Mendelian randomization (MR) study. RESULTS: In the cross-sectional study, 19,091 non-frailty participants and 5878 frailty participants were included in this study. We observed a significant positive association between osteoporosis and frailty after adjusting for demographic characteristics, body mass index (BMI), smoking, and alcohol use (OR = 1.454, 95% CI [1.142,1.851], P = 0.003). Moreover, the MR study showed a bidirectional causal relationship between osteoporosis and frailty. When osteoporosis was used as an exposure factor, the frailty pooled OR value calculated utilizing the inverse variance weighted (IVW) method was 2.81 (95% CI [1.69, 4.68], P = 6.82 × 10- 5). When frailty was used as an exposure factor, the OR value calculated using the IVW method was 1.01 (95% CI [1.00,1.01], P = 3.65 × 10- 7). CONCLUSIONS: Osteoporosis was positively correlated with frailty, and the results remained robust after adjusting for covariates. Further, MR studies have shown a bidirectional causal relationship between osteoporosis and frailty.

Risk prediction models for diabetic nephropathy among type 2 diabetes patients in China: a systematic review and meta-analysis.

Objective: This study systematically reviews and meta-analyzes existing risk prediction models for diabetic kidney disease (DKD) among patients with type 2 diabetes, aiming to provide references for scholars in China to develop higher-quality risk prediction models. Methods: We searched databases including China National Knowledge Infrastructure (CNKI), Wanfang Data, VIP Chinese Science and Technology Journal Database, Chinese Biomedical Literature Database (CBM), PubMed, Web of Science, Embase, and the Cochrane Library for studies on the construction of DKD risk prediction models among type 2 diabetes patients, up until 28 December 2023. Two researchers independently screened the literature and extracted and evaluated information according to a data extraction form and bias risk assessment tool for prediction model studies. The area under the curve (AUC) values of the models were meta-analyzed using STATA 14.0 software. Results: A total of 32 studies were included, with 31 performing internal validation and 22 reporting calibration. The incidence rate of DKD among patients with type 2 diabetes ranged from 6.0% to 62.3%. The AUC ranged from 0.713 to 0.949, indicating the prediction models have fair to excellent prediction accuracy. The overall applicability of the included studies was good; however, there was a high overall risk of bias, mainly due to the retrospective nature of most studies, unreasonable sample sizes, and studies conducted in a single center. Meta-analysis of the models yielded a combined AUC of 0.810 (95% CI: 0.780-0.840), indicating good predictive performance. Conclusion: Research on DKD risk prediction models for patients with type 2 diabetes in China is still in its initial stages, with a high overall risk of bias and a lack of clinical application. Future efforts could focus on constructing high-performance, easy-to-use prediction models based on interpretable machine learning methods and applying them in clinical settings. Registration: This systematic review and meta-analysis was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement, a recognized guideline for such research. Systematic review registration: https://www.crd.york.ac.uk/prospero/, identifier CRD42024498015.

Discovering potential mechanisms of intervertebral disc disease using systematic Mendelian randomization of human circulating immunocytomics.

BACKGROUND: Although intervertebral disc degeneration (IVDD) is a critical factor in many spine-related diseases and has an extremely high prevalence in the aging population, the potential pathogenesis remains to be clarified entirely. Immune cells have been found to perform an essential function during the onset and progression of IVDD in recent years. Therefore, we explored the association between immune cell characteristics and IVDD through Mendelian randomization (MR) analysis and further delved into the mediating role of potential metabolites. METHODS: Based on the MR analysis, the association of 731 immune cell phenotypes and 1400 metabolites on IVDD were assessed. Single nucleotide polymorphisms (SNPs) were closely associated the expression levels of immune cell characteristics and the concentrations of metabolites and have been used as instrumental variables (IVs) for deducing them as risk factors or protective factors for IVDD. In addition, mediation analyses have been performed to identify potential metabolite mediators between immune cell characteristics and IVDD. RESULTS: MR analysis identified 27 immune cell phenotypes and 79 metabolites significantly associated with IVDD. In addition, mediation analysis was performed by selecting the immune cell phenotype that most significantly increased the risk of IVDD - CD86 on monocytes. A total of four metabolite-mediated mediation relationships were revealed (3b-hydroxy-5-cholenoic acid, X-22509, N-acetyl-L-glutamine, and N2-acetyl, N6, N6-dimethyllysine). CONCLUSION: The findings of this analysis identified underlying association between immune cell phenotypes, metabolite, and IVDD that may serve as predictive and prognostic clinical biomarkers and benefit IVDD pathogenesis research.

Therapeutic potential of single-nucleotide polymorphism-mediated IL6R inhibitors in ankylosing spondylitis treatment.

Objective: Interleukin-6 (IL-6) is a multiple-effect cell factor implicated in the etiopathogenesis of several rheumatologic disorders. The blockade of the IL-6 pathway via IL6R inhibitors effectively treats these disorders. However, the clinical significance of the IL6R blockade for ankylosing spondylitis (AS) therapy remains controversial. With advances in genomics, increasing evidence has revealed the role of heritability in the etiology of disease, and Mendelian randomization (MR) analyses are being used more broadly to infer causation. Therefore, this MR study aims to evaluate the potential therapeutic utility of IL6R-targeted approaches in AS. Methods: The C-reactive protein (CRP) level was used as an exposure factor, and rheumatoid arthritis (RA) was used as a positive control. As-related genome-wide association study (GWAS) data were used as the primary outcome of drug-targeted MR analyses to test the relation between IL6R blockers and AS. Inverse variance weighting (IVW) is the primary analytical approach. Various sensitivity tests were performed to check the robustness and trustworthiness of the causality estimation, including consistency, heterogeneity, and pleiotropy analyses. In addition, repeated analysis was conducted using different GWAS data related to exposures and outcomes to examine the results for stability. Results: According to the IVW results, IL6R inhibitors significantly reduced the risk of AS in ukb-b-18194 (OR: 0.995, 95% CI 0.993-0.996, P = 5.12 × 10-08) and ukb-a-88 (OR: 0.994, 95% CI 0.993-0.996, P = 6.25 × 10-15). Moreover, repeated analyses were performed using different exposure-related GWAS data, yielding similar results, ukb-b-18194 (OR: 0.995, 95% CI 0.993-0.997, P = 1.25 × 10-06) and ukb-a-88 (OR: 0.995, 95% CI 0.994-0.997, P = 7.81 × 10-09). Heterogeneity analyses and pleiotropy analyses indicated no significant heterogeneity or pleiotropy. Conclusion: This MR analysis result further validates that the IL-6 pathway may contribute to the pathogenesis of AS and that the inhibition of IL6R reduces the risk of AS. These findings may guide future studies and provide more favorable drug treatment options for people at high risk of AS.

Electroacupuncture Suppresses Oxidative Stress and Ferroptosis by Activating the mTOR/SREBP1 Pathway in Ischemic Stroke.

Ischemic stroke (IS) is one of the leading causes of death and disability worldwide. Electroacupuncture (EA) has been shown to exert a neuroprotective effect in IS. However, its specific anti-IS mechanisms remain to be fully elucidated. By constructing a rat IS (middle cerebral artery occlusion, or MCAO) model and performing EA treatment, neurological deficit score, brain water content, and cerebral infarction were evaluated. ELISA was used to measure the levels of oxidative stress-related molecules (MDA, SOD, GSH, and CAT). Ferroptosis-related proteins (GPX4, SLC7A11, TfR1, L-ferritin, and hepcidin), neurological damage-related proteins (GFAP, Iba-1, and Nestin), α7nAChR, and mTOR pathway-related proteins (mTOR, p-mTOR, and SREBP1) in the rat brain penumbra were assessed by western blotting. Following EA treatment, neurological deficit scores, brain water content, cerebral infarction area, and GFAP, Iba-1, and Nestin expression were reduced. Additionally, EA treatment decreased MDA and increased SOD, GSH, and CAT. Moreover, the rats showed elevated GPX4 and SLC7A11 and lowered TfR1, L-ferritin, and hepcidin. In contrast, a7nAChR, mTOR, p-mTOR, and SREBP1 expression were upregulated. EA treatment inhibited OS and ferroptosis to exert a neuroprotective effect in IS, which might be realized via the activation of mTOR/SREBP1 signaling.

Callicarpayongshunensis (Lamiaceae): A new species from Hunan, China.

This study provides detailed description of a newly-discovered Callicarpayongshunensis Wen B. Xu, Xiao D. Li & Yan Ling Liu (Lamiaceae) species from Hunan, China. The species shares similarities in the inflorescence, glandular colour and leaf shape features with C.luteopunctata H. T. Chang and C.giraldii Hesse ex Rehd., while its white fruits are similar to those of C.longifolia Lamk. However, its procumbent, evergreen shrub and white fruits are distinctly different from those of C.luteopunctata and C.giraldii, while its procumbent, scarless nodes and stellate pubescence free fruits distinguishes it from C.longifolia. Images, distribution, morphological features, molecular phylogenetic classification and conservation assessment of this new Callicarpa species are explored.

l-arginine promotes angio-osteogenesis to enhance oxidative stress-inhibited bone formation by ameliorating mitophagy.

Background: Osteoporosis is one of the most common bone diseases in middle-aged and elderly populations worldwide. The development of new drugs to treat the disease is a key focus of research. Current treatments for osteoporosis are mainly directed at promoting osteoblasts and inhibiting osteoclasts. However, there is currently no ideal approach for osteoporosis treatment. l-arginine is a semi-essential amino acid involved in a number of cellular processes, including nitric production, protein biosynthesis, and immune responses. We previously reported that l-arginine-derived compounds can play a regulatory role in bone homeostasis. Purpose: To investigate the specific effect of l-arginine on bone homeostasis. Methods: Mildly aged and ovariectomized mouse models were used to study the effects of l-arginine on osteogenesis and angiogenesis, assessed by micro-computed tomography and immunostaining of bone tissue. The effect of l-arginine on osteogenesis, angiogenesis, and adipogenesis was further studied in vitro using osteoblasts obtained from cranial cap bone, endothelial cells, and an adipogenic cell line. Specific methods to assess these processes included lipid staining, cell migration, tube-forming, and wound-healing assays. Protein and mRNA expression was determined for select biomarkers. Results: We found that l-arginine attenuated bone loss and promoted osteogenesis and angiogenesis. l-arginine increased the activity of vascular endothelial cells, whereas it inhibited adipogenesis in vitro. In addition, we found that l-arginine altered the expression of PINK1/Parkin and Bnip3 in the mitochondria of osteoblast-lineage and endothelial cells, thereby promoting mitophagy and protecting cells from ROS. Similarly, l-arginine treatment effectively ameliorated osteoporosis in an ovariectomized mouse model. Conclusion: l-arginine promotes angio-osteogenesis, and inhibits adipogenesis, effects mediated by the PINK1/Parkin- and Bnip3-mediated mitophagy. The Translational Potential of this Article: L-arginine supplementation may be an effective adjunct therapy in the treatment of osteoporosis.

Indisulam synergizes with melphalan to inhibit Multiple Myeloma malignancy via targeting TOP2A.

Multiple myeloma (MM) is the second most prevalent hematologic malignancy which remains uncurable. Numerous drugs have been discovered to inhibit MM cells. Indisulam, an aryl sulfonamide, has a potent anti-myeloma activity in vitro and in vivo. This study aims to explore the new mechanism of indisulam and investigate its potential use in combination with melphalan. We examined DNA damage in MM cells through various methods such as western blotting (WB), immunofluorescence, and comet assay. We also identified the role of topoisomerase IIα (TOP2A) using bioinformatic analyses. The impact of indisulam on the RNA and protein levels of TOP2A was investigated through qPCR and WB. Cell proliferation and apoptosis were assessed using CCK-8 assays, Annexin V/PI assays and WB. We predicted the synergistic effect of the combination treatment based on calculations performed on a website, and further explored the effect of indisulam in combination with melphalan on MM cell lines and xenografts. RNA sequencing data and basic experiments indicated that indisulam caused DNA damage and inhibited TOP2A expression by decreasing transcription and promoting degradation via the proteasome pathway. Functional experiments revealed that silencing TOP2A inhibited cell proliferation and induced apoptosis and DNA damage. Finally, Indisulam/melphalan combination treatment demonstrated a strong synergistic anti-tumor effect compared to single-agent treatments in vitro and in vivo. These findings suggest that combination therapies incorporating indisulam and melphalan have the potential to enhance treatment outcomes for MM.

IRF4-BLOC1S5: the first rearrangement gene identified in TEMPI syndrome.

Not available.

A novel method for simultaneous detection of hematological tumors and infectious pathogens by metagenomic next generation sequencing of plasma.

BACKGROUND: Metagenomic next-generation sequencing (mNGS) is valuable for pathogen identification; however, distinguishing between infectious diseases and conditions with potentially similar clinical manifestations, including malignant tumors, is challenging. Therefore, we developed a method for simultaneous detection of infectious pathogens and cancer in blood samples. METHODS: Plasma samples (n = 244) were collected from 150 and 94 patients with infections and hematological malignancies, respectively, and analyzed by mNGS for pathogen detection, alongside human tumor chromosomal copy number variation (CNV) analysis (≥5Mbp or 10Mbp CNV region). Further, an evaluation set, comprising 87 plasma samples, was analyzed by mNGS and human CNV analysis, to validate the feasibility of the method. RESULTS: Among 94 patients with hematological malignancy, sensitivity values of CNV detection for tumor diagnosis were 69.15 % and 32.98 % for CNV region 5Mbp and 10Mbp, respectively, with corresponding specificities of 92.62 % and 100 % in the infection group. Area under the ROC curve (AUC) values for 5Mbp and 10Mbp region were 0.825 and 0.665, respectively, which was a significant difference of 0.160 (95 % CI: 0.110-0.210; p < 0.001), highlighting the superiority of 5Mbp output region data. Six patients with high-risk CNV results were identified in the validation study: three with history of tumor treatment, two eventually newly-diagnosed with hematological malignancies, and one with indeterminate final diagnosis. CONCLUSIONS: Concurrent CNV analysis alongside mNGS for infection diagnosis is promising for detecting malignant tumors. We recommend adopting a CNV region of 10Mbp over 5Mbp for our model, because of the lower false-positive rate (FPR).

Electroacupuncture Alleviates Post-stroke Cognitive Impairment Through Inhibiting miR-135a-5p/mTOR/NLRP3 Axis-mediated Autophagy.

Post-stroke cognitive impairment is a significant challenge with limited treatment options. Electroacupuncture (EA) has shown promise in improving cognitive function after stroke. Our study explores the underlying mechanism of EA in alleviating cognitive impairment through the inhibition of autophagy. We utilized a rat model of stroke induced by middle cerebral artery occlusion (MCAO) to evaluate the efficacy of EA. Treatment with EA was observed to markedly improve cognitive function and reduce inflammation in MCAO rats, as evidenced by decreased neurological deficit scores, shorter latencies in the water maze test, and diminished infarct volumes. EA also attenuated tissue damage in the hippocampus and lowered the levels of pro-inflammatory cytokines and oxidative stress markers. Although autophagy was upregulated in MCAO rats, EA treatment suppressed this process, indicated by a reduction in autophagosome formation and alteration of autophagy-related protein expression. The protective effects of EA were reversed by the autophagy activator rapamycin. EA treatment elevated the levels of microRNA (miR)-135a-5p expression, and suppression of this elevation attenuated the remedial efficacy of EA in addressing cognitive impairment and inflammation. MiR-135a-5p targeted mammalian target of rapamycin (mTOR)/NOD-like receptor protein 3 (NLRP3) signaling to repress autophagy. EA treatment inhibits autophagy and alleviates cognitive impairment in post-stroke rats. It exerts its beneficial effects by upregulating miR-135a-5p and targeting the mTOR/NLRP3 axis.

External validation of the prediction model of intradialytic hypotension: a multicenter prospective cohort study.

OBJECTIVE: Intradialytic hypotension (IDH) is a common and serious complication in patients with Maintenance Hemodialysis (MHD). The purpose of this study is to externally verify three IDH risk prediction models recently developed by Ma et al. and recalibrate, update and present the optimal model to improve the accuracy and applicability of the model in clinical environment. METHODS: A multicenter prospective cohort study of patients from 11 hemodialysis centers in Sichuan Province, China, was conducted using convenience sampling from March 2022 to July 2022, with a follow-up period of 1 month. Model performance was assessed by: (1) Discrimination: Evaluated through the computation of the Area Under Curve (AUC) and its corresponding 95% confidence intervals. (2) Calibration: scrutinized through visual inspection of the calibration plot and utilization of the Brier score. (3) The incremental value of risk prediction and the utility of updating the model were gauged using NRI (Net Reclassification Improvement) and IDI (Integrated Discrimination Improvement). Decision Curve Analysis (DCA) was employed to evaluate the clinical benefit of updating the model. RESULTS: The final cohort comprised 2235 individuals undergoing maintenance hemodialysis, exhibiting a 14.6% occurrence rate of IDH. The externally validated Area Under the Curve (AUC) values for the three original prediction models were 0.746 (95% CI: 0.718 to 0.775), 0.709 (95% CI: 0.679 to 0.739), and 0.735 (95% CI: 0.706 to 0.764) respectively. Conversely, the AUC value for the recalibrated and updated columnar plot model reached 0.817 (95% CI: 0.791 to 0.842), accompanied by a Brier score of 0.081. Furthermore, Decision Curve Analysis (DCA) exhibited a net benefit within the threshold probability range of 15.2% to 87.1%. CONCLUSION: Externally validated, recalibrated, updated, and presented IDH prediction models may serve as a valuable instrument for evaluating IDH risk in clinical practice. Furthermore, they hold the potential to guide clinical providers in discerning individuals at risk and facilitating judicious clinical intervention decisions.

Discovering High Entropy Alloy Electrocatalysts in Vast Composition Spaces with Multiobjective Optimization.

High entropy alloys (HEAs) are a highly promising class of materials for electrocatalysis as their unique active site distributions break the scaling relations that limit the activity of conventional transition metal catalysts. Existing Bayesian optimization (BO)-based virtual screening approaches focus on catalytic activity as the sole objective and correspondingly tend to identify promising materials that are unlikely to be entropically stabilized. Here, we overcome this limitation with a multiobjective BO framework for HEAs that simultaneously targets activity, cost-effectiveness, and entropic stabilization. With diversity-guided batch selection further boosting its data efficiency, the framework readily identifies numerous promising candidates for the oxygen reduction reaction that strike the balance between all three objectives in hitherto unchartered HEA design spaces comprising up to 10 elements.

An edge cloud and Fibonacci-Diffie-Hellman encryption scheme for secure printer data transmission.

Network printers face increasing security threats from network attacks that can lead to sensitive information leakage and data tampering. To address these risks, we propose a novel Fibonacci-Diffie-Hellman (FIB-DH) encryption scheme using edge cloud collaboration. Our approach utilizes properties of third-order Fibonacci matrices combined with the Diffie-Hellman key exchange to encrypt printer data transmissions. The encrypted data is transmitted via edge cloud servers and verified by the receiver using inverse Fibonacci transforms. Our experiments demonstrate that the FIB-DH scheme can effectively improve printer data transmission security against common attacks compared to conventional methods. The results show reduced vulnerabilities to leakage and tampering attacks in our approach. This work provides an innovative application of cryptographic techniques to strengthen security for network printer communications.

A nomogram prediction model for mild cognitive impairment in non-dialysis outpatient patients with chronic kidney disease.

BACKGROUND: The high prevalence of mild cognitive impairment (MCI) in non-dialysis individuals with chronic kidney disease (CKD) impacts their prognosis and quality of life. OBJECTIVE: This study aims to investigate the variables associated with MCI in non-dialysis outpatient patients with CKD and to construct and verify a nomogram prediction model. METHODS: 416 participants selected from two hospitals in Chengdu, between January 2023 and June 2023. They were categorized into two groups: the MCI group (n = 210) and the non-MCI (n = 206). Univariate and multivariate binary logistic regression analyses were employed to identify independent influences (candidate predictor variables). Subsequently, regression models was constructed, and a nomogram was drawn. The restricted cubic spline diagram was drawn to further analyze the relationship between the continuous numerical variables and MCI. Internally validated using a bootstrap resampling procedure. RESULTS: Among 416 patients, 210 (50.9%) had MCI. Logistic regression analysis revealed that age, educational level, occupational status, use of smartphones, sleep disorder, and hemoglobin were independent influencing factors of MCI (all p<.05). The model's area under the curve was 0.926,95% CI (0.902, 0.951), which was a good discriminatory measure; the Calibration curve, the Hosmer-Lemeshow test, and the Clinical Decision Curve suggested that the model had good calibration and clinical benefit. Internal validation results showed the consistency index was 0.926, 95%CI (0.925, 0.927). CONCLUSION: The nomogram prediction model demonstrates good performance and can be used for early screening and prediction of MCI in non-dialysis patients with CKD. It provides valuable reference for medical staff to formulate corresponding intervention strategies.

Oncoprotein SET-associated transcription factor ZBTB11 triggers lung cancer metastasis.

Metastasis is the major cause of lung cancer-related death, but the mechanisms governing lung tumor metastasis remain incompletely elucidated. SE translocation (SET) is overexpressed in lung tumors and correlates with unfavorable prognosis. Here we uncover SET-associated transcription factor, zinc finger and BTB domain-containing protein 11 (ZBTB11), as a prometastatic regulator in lung tumors. SET interacts and collaborates with ZBTB11 to promote lung cancer cell migration and invasion, primarily through SET-ZBTB11 complex-mediated transcriptional activation of matrix metalloproteinase-9 (MMP9). Additionally, by transcriptional repression of proline-rich Gla protein 2 (PRRG2), ZBTB11 links Yes-associated protein 1 (YAP1) activation to drive lung tumor metastasis independently of SET-ZBTB11 complex. Loss of ZBTB11 suppresses distal metastasis in a lung tumor mouse model. Overexpression of ZBTB11 is recapitulated in human metastatic lung tumors and correlates with diminished survival. Our study demonstrates ZBTB11 as a key metastatic regulator and reveals diverse mechanisms by which ZBTB11 modulates lung tumor metastasis.

Comparing Outcomes of Banana-Shaped and Straight Cages in Transforaminal Lumbar Interbody Fusion for Lumbar Degenerative Diseases: A Systematic Review and Meta-Analysis.

OBJECTIVE: This meta-analysis aims to refine the understanding of the optimal choice between different cage shapes in transforaminal lumbar interbody fusion (TLIF) by systematically comparing perioperative data, radiological outcomes, clinical results, and complications associated with banana-shaped and straight bullet cages. METHODS: A meticulous literature search encompassing PubMed, Embase, Scopus, Web of Science, China Knowledge Network, and Wanfang Data was executed up to October 5, 2023. Inclusion criteria focused on studies comparing banana-shaped and straight bullet cages in TLIF. The quality of included studies was assessed using appropriate tools such as the Newcastle-Ottawa Scale (NOS) for nonrandomized studies. Rigorous evaluations were performed for radiographic outcomes, including disc height (DH), segmental lordosis (SL), lumbar lordosis (LL), subsidence, and fusion rates. Clinical outcomes were meticulously evaluated using visual analogue scale (VAS), Oswestry Disability Index (ODI), and complications. RESULTS: The analysis incorporated 7 studies, involving 573 patients (297 with banana-shaped cages, 276 with straight cages), all with NOS ratings exceeding 5 stars. No statistically significant differences were observed in operative time, blood loss, or hospitalization between the 2 cage shapes. Banana-shaped cages exhibited greater changes in DH (p = 0.001), SL (p = 0.02), and LL (p = 0.01). Despite statistically higher changes in ODI for straight cages (26.33, p < 0.0001), the actual value remained similar to banana-shaped cages (26.15). Both cage types demonstrated similar efficacy in VAS, complication rates, subsidence, and fusion rates. CONCLUSION: Although banana-shaped cages can excel in restoring DH, SL, and LL, straight bullet cages can provide comparable functional improvements, pain relief, and complication rates.