Association between ASPECTS region of infarction and clinical outcome in non-acute large vessel occlusion ischaemic stroke after endovascular recanalisation.

PURPOSE: This study retrospectively investigated whether infarction in specific Alberta Stroke Program Early CT Score (ASPECTS) regions is associated with clinical outcome in patients with symptomatic non-acute internal carotid or middle cerebral artery occlusion who underwent endovascular recanalisation (ER). METHODS: Preoperative ASPECTS and region of infarction were recorded before recanalisation. Clinical outcome was evaluated 90 days after the procedure using the modified Rankin Scale; a score>2 was defined as poor outcome. Secondary outcomes included postprocedural cerebral oedema, intracranial haemorrhage (ICH) and symptomatic ICH. RESULTS: Among the 86 patients included, 90-day outcome was poor in 30 (34.9%) and 40 experienced cerebral oedema (46.5%). Multivariate logistic regression models showed that lenticular nucleus infarction (OR 19.61-26.00, p<0.05), admission diastolic blood pressure (OR 1.07-1.08, p<0.05), preprocedural National Institutes of Health Stroke Scale (OR 1.96-2.05, p<0.001) and haemorrhagic transformation (OR 14.99-18.81, p<0.05) were independent predictors of poor 90-day outcome. The area under the receiver operating characteristic curve for lenticular nucleus infarction as a predictor of poor outcome was 0.73. M2 region infarction (OR 26.07, p<0.001) and low American Society of Interventional and Therapeutic Neuroradiology/Society of Interventional Radiology collateral circulation grade (OR 0.16, p=0.001) were independent predictors of postprocedural cerebral oedema. The area under the receiver operating characteristic curve for M2 region infarction as a predictor of cerebral oedema was 0.64. Region of infarction did not significantly differ between patients with and without postprocedural ICH or symptomatic ICH. CONCLUSIONS: Lenticular nucleus and M2 region infarction were independent predictors of poor 90-day outcome and postprocedural cerebral oedema, respectively, in patients with non-acute anterior circulation large artery occlusion who underwent ER.

Homocysteine Metabolism, Subclinical Myocardial Injury, and Cardiovascular Mortality in the General Population.

Background: Homocysteine (Hcy) is a recognized cardiovascular disease (CVD) risk factor linked with atherosclerosis. However, the association between Hcy and myocardial injury is little known. Objectives: This study aimed to examine the associations between Hcy metabolism, subclinical myocardial injury, and cardiovascular mortality. Methods: We included 10,871 participants without diagnosed CVD. Generalized linear regression was used to investigate the relationship between Hcy-related indicators (plasma total Hcy [tHcy], vitamin B12, and folate) and myocardial injury biomarkers (high-sensitivity troponin T [hs-cTnT], high-sensitivity troponin I [hs-cTnI] measured using 3 assays [Abbott, Siemens, and Ortho], and N-terminal pro-B-type natriuretic peptide [NT-proBNP]). Results: Among 10,871 participants, the weighted mean levels for tHcy, folate, and vitamin B12 were 8.58 µmol/L, 32.43 nmol/L, and 447.08 pmol/L, respectively. Plasma tHcy levels were positively associated with elevated hs-cTnT, hs-cTnI, and NT-proBNP, whereas folate and vitamin B12 were not inversely related to myocardial injury biomarkers. Multivariable-adjusted odds ratios for elevated hs-cTnT (19 ng/L) and NT-proBNP (125 pg/mL) per doubling of tHcy were 2.80 (95% CI: 1.17-6.73; P < 0.001) and 1.58 (95% CI: 1.20-2.08; P < 0.001), respectively. The associations of tHcy levels with elevated hs-cTnI (Abbott: 28 ng/L; Siemens: 46.5 ng/L; Ortho: 11 ng/L) were consistent. Indirect effects of tHcy on cardiovascular mortality risk via hs-cTnT and NT-proBNP explained up to 26.6% and 12.3% of the total effect, respectively. Conclusions: Plasma tHcy, not folate or vitamin B12, is significantly associated with elevated hs-cTnT, hs-cTnI, and NT-proBNP in adults without CVD. Subclinical myocardial injury may substantially mediate Hcy-related cardiovascular mortality risk.

Diverse roles of aldolase enzymes in cancer development, drug resistance and therapeutic approaches as moonlighting enzymes.

Aldolase enzymes, particularly ALDOA, ALDOB, and ALDOC, play a crucial role in the development and progression of cancer. While the aldolase family is mainly known for its involvement in the glycolysis pathway, these enzymes also have various pathological and physiological functions through distinct signaling pathways such as Wnt/ß-catenin, EGFR/MAPK, Akt, and HIF-1α. This has garnered increased attention in recent years and shed light on other sides of this enzyme. Potential therapeutic strategies targeting aldolases include using siRNA, inhibitors like naphthol AS-E phosphate and TX-2098, and natural compounds such as HDPS-4II and L-carnosine. Additionally, anticancer peptides derived from ALDOA, like P04, can potentially increase cancer cells' sensitivity to chemotherapy. Aldolases also affect cancer drug resistance by different approaches, making them good therapeutic targets. In this review, we extensively explore the role of aldolase enzymes in various types of cancers in proliferation, invasion, migration, and drug resistance; we also significantly explore the possible treatment considering aldolase function.

A transcriptional regulatory mechanism of genes in the tricarboxylic acid cycle in the heart.

The tricarboxylic acid (TCA) cycle plays a crucial role in mitochondrial ATP production in the healthy heart. However, in heart failure, the TCA cycle becomes dysregulated. Understanding the mechanism by which TCA cycle genes are transcribed in the healthy heart is an important prerequisite to understanding how these genes become dysregulated in the failing heart. PPARγ coactivator 1α (PGC-1α) is a transcriptional coactivator that broadly induces genes involved in mitochondrial ATP production. PGC-1α potentiates its effects through the coactivation of coupled transcription factors, such as estrogen-related receptor (ERR), nuclear respiratory factor 1 (Nrf1), GA-binding protein-a (Gabpa), and Yin Yang 1 (YY1). We hypothesized that PGC-1α plays an essential role in the transcription of TCA cycle genes. Thus, utilizing localization peaks of PGC-1α to TCA cycle gene promoters would allow the identification of coupled transcription factors. PGC-1α potentiated the transcription of 13 out of 14 TCA cycle genes, partly through ERR, Nrf1, Gabpa, and YY1. ChIP-sequencing showed PGC-1α localization peaks in TCA cycle gene promoters. Transcription factors with binding elements that were found proximal to PGC-1α peak localization were generally essential for the transcription of the gene. These transcription factor binding elements were well conserved between mice and humans. Among the four transcription factors, ERR and Gabpa played a major role in potentiating transcription when compared to Nrf1 and YY1. These transcription factor-dependent PGC-1α recruitment was verified with Idh3a, Idh3g, and Sdha promoters with DNA binding assay. Taken together, this study clarifies the mechanism by which TCA cycle genes are transcribed, which could be useful in understanding how those genes are dysregulated in pathological conditions.

Association between sodium-glucose cotransporter 2 inhibitors and eye disorders: a systematic review and meta-analysis.

INTRODUCTION: Lowering blood glucose is important to prevent long-term microvascular complications in adults with type 2 diabetes mellitus (T2DM). Various evidence suggests that sodium-glucose cotransporter 2 (SGLT2) inhibitors are beneficial for microvascular diseases. This study was designed to investigate whether SGLT2 inhibitors have an effect on eye disorders. METHODS: We searched PubMed, Web of Science, and ClinicalTrials.gov for randomized, double-blind, placebo-controlled trials with at least 24 weeks of follow-up up to 20 December 2023. Mantel-Haenszel statistical method, risk ratios (RRs) and 95% confidence intervals (CIs) were used to analyze the binary variables. RESULTS: We included a total of 40 studies covering 104,586 participants. T2DM was present in 84.5% of the subjects. SGLT2 inhibitors had no significant effect on overall eye events compared to placebo (RR 0.99; 95%CI 0.86-1.15; p = 0.91), nor did subgroup analysis. We did not observe significant heterogeneity (I2 = 0; p = 0.99). Analysis of all secondary outcomes showed that SGLT2 inhibitors did not cause a significantly different effect from placebo. Meta-analysis in the entire T2DM population showed results consistent with those in the overall population. CONCLUSION: SGLT2 inhibitors did not have a significant effect on eye disorders during treatment, regardless of baseline conditions and duration of treatment.

Effect of different approaches of direct radiation on the surface structure and caries susceptibility of enamel.

It is not clear whether different radiation methods have different effects on enamel. The purpose of this study was to compare the effects of single and fractionated radiation on enamel and caries susceptibility and to provide an experimental basis for further study of radiation­related caries. Thirty-six caries-free human third molars were collected and randomly divided into three groups (n = 12). Group1 (control group) was not exposed to radiation. Group 2 received single radiation with a cumulative dose of 70 Gy. Group 3 underwent fractionated radiation, receiving 2 Gy/day for 5 days followed by a 2-day rest period, for a total of 7 weeks with a cumulative dose of 70 Gy. Changes in microhardness, roughness, surface morphology, bacterial adhesion and ability of acid resistance of each group were tested. Scanning electron microscope revealed that the enamel surface in both radiation groups exhibited unevenness and cracks. Compared with the control group, microhardness and acid resistance of enamel decreased, while roughness and bacterial adhesion increased in both the single radiation and fractionated radiation groups. Compared with the single radiation group, the enamel surface microhardness and acid resistance decreased in the fractionated radiation group, while roughness and bacterial adhesion increased. Both single radiation and fractionated radiation resulting in changes in the physical and biological properties of enamel, with these changes being more pronounced in the fractionated radiation group. Therefore, fractionated radiation is recommended as a more suitable method for constructing a radiation­related caries model in vitro.

A transformer-based multi-task deep learning model for simultaneous T-stage identification and segmentation of nasopharyngeal carcinoma.

Background: Accurate tumor target contouring and T staging are vital for precision radiation therapy in nasopharyngeal carcinoma (NPC). Identifying T-stage and contouring the Gross tumor volume (GTV) manually is a laborious and highly time-consuming process. Previous deep learning-based studies have mainly been focused on tumor segmentation, and few studies have specifically addressed the tumor staging of NPC. Objectives: To bridge this gap, we aim to devise a model that can simultaneously identify T-stage and perform accurate segmentation of GTV in NPC. Materials and methods: We have developed a transformer-based multi-task deep learning model that can perform two tasks simultaneously: delineating the tumor contour and identifying T-stage. Our retrospective study involved contrast-enhanced T1-weighted images (CE-T1WI) of 320 NPC patients (T-stage: T1-T4) collected between 2017 and 2020 at our institution, which were randomly allocated into three cohorts for three-fold cross-validations, and conducted the external validation using an independent test set. We evaluated the predictive performance using the area under the receiver operating characteristic curve (ROC-AUC) and accuracy (ACC), with a 95% confidence interval (CI), and the contouring performance using the Dice similarity coefficient (DSC) and average surface distance (ASD). Results: Our multi-task model exhibited sound performance in GTV contouring (median DSC: 0.74; ASD: 0.97 mm) and T staging (AUC: 0.85, 95% CI: 0.82-0.87) across 320 patients. In early T category tumors, the model achieved a median DSC of 0.74 and ASD of 0.98 mm, while in advanced T category tumors, it reached a median DSC of 0.74 and ASD of 0.96 mm. The accuracy of automated T staging was 76% (126 of 166) for early stages (T1-T2) and 64% (99 of 154) for advanced stages (T3-T4). Moreover, experimental results show that our multi-task model outperformed the other single-task models. Conclusions: This study emphasized the potential of multi-task model for simultaneously delineating the tumor contour and identifying T-stage. The multi-task model harnesses the synergy between these interrelated learning tasks, leading to improvements in the performance of both tasks. The performance demonstrates the potential of our work for delineating the tumor contour and identifying T-stage and suggests that it can be a practical tool for supporting clinical precision radiation therapy.

DNA barcoding combined with high-resolution melting analysis to discriminate rhubarb species and its traditional Chinese patent medicines.

Introduction: Rhubarb is a frequently used and beneficial traditional Chinese medicine. Wild resources of these plants are constantly being depleted, meaning that rhubarb products have been subjected to an unparalleled level of adulteration. Consequentially, reliable technology is urgently required to verify the authenticity of rhubarb raw materials and commercial botanical drugs. Methods: In this study, the barcode-DNA high-resolution melting (Bar-HRM) method was applied to characterize 63 rhubarb samples (five Polygonaceae species: Rheum tanguticum, Rh. palmatum, Rh. officinale, Rumex japonicus and Ru. sp.) and distinguish the rhubarb contents of 24 traditional Chinese patent medicine (TCPM) samples. Three markers, namely ITS2, rbcL and psbA-trnH, were tested to assess the candidate DNA barcodes for their effectiveness in distinguishing rhubarb from its adulterants. A segment from ITS2 was selected as the most suitable mini-barcode to identify the botanical drug rhubarb in TCPMs. Then, rhubarbs and TCPM samples were subjected to HRM analysis based on the ITS2 barcode. Results: Among the tested barcoding loci, ITS2 displayed abundant sites of variation and was effective in identifying Polygonaceae species and their botanical origins. HRM analysis based on the ITS2 mini-barcode region successfully distinguished the authenticity of five Polygonaceae species and eight batches of TCPMs. Of the 18 TCPM samples, 66.7 % (12 samples) were identified as containing Rh. tanguticum or Rh. officinale. However, 33.3 % were shown to consist of adulterants. Conclusions: These results demonstrated that DNA barcoding combined with HRM is a specific, suitable and powerful approach for identifying rhubarb species and TCPMs, which is crucial to guaranteeing the security of medicinal plants being traded internationally.

Aptamer Screening: Current Methods and Future Trend towards Non-SELEX Approach.

Aptamers are nucleic acid sequences that specifically bind with target molecules and are vital to applications such as biosensing, drug development, disease diagnostics, etc. The traditional selection procedure of aptamers is based on the Systematic Evolution of Ligands by an Exponential Enrichment (SELEX) process, which relies on repeating cycles of screening and amplification. With the rapid development of aptamer applications, RNA and XNA aptamers draw more attention than before. But their selection is troublesome due to the necessary reverse transcription and transcription process (RNA) or low efficiency and accuracy of enzymes for amplification (XNA). In light of this, we review the recent advances in aptamer selection methods and give an outlook on future development in a non-SELEX approach, which simplifies the procedure and reduces the experimental costs. We first provide an overview of the traditional SELEX methods mostly designed for screening DNA aptamers to introduce the common tools and methods. Then a section on the current screening methods for RNA and XNA is prepared to demonstrate the efforts put into screening these aptamers and the current difficulties. We further predict that the future trend of aptamer selection lies in non-SELEX methods that do not require nucleic acid amplification. We divide non-SELEX methods into an immobilized format and non-immobilized format and discuss how high-resolution partitioning methods could facilitate the further improvement of selection efficiency and accuracy.

A thermodynamic model of the surface hydroxylation of γ-Al2O3.

Rational design of γ-alumina-based catalysts relies on an extensive understanding of the distribution of hydroxyl groups on the surface of γ-alumina and their physicochemical properties, which remain unclear and challenging to determine experimentally due to the structural complexity. In this work, by means of DFT and thermodynamic calculations, various hydroxylation modes of γ-alumina (110) and (100) surfaces at different OH coverages were evaluated, based on which a thermodynamic model to reflect the relationship between temperature and the surface structure was established and the stable hydroxylation modes under experimental conditions were predicted. This enables us to identify the experimentally measured IR spectra. The effect of hydroxyl coverages on the surface Lewis acidity was then analyzed, showing that the presence of hydroxyl groups could promote the Lewis acidity of neighboring Al sites. This work provides fundamental insights into the molecular level understanding of the surface properties of γ-alumina and benefits the rational design of alumina-based catalysts.

Prediction of the short-term efficacy and recurrence of photodynamic therapy in the treatment of oral leukoplakia based on deep learning.

BACKGROUND: The treatment of oral leukoplakia (OLK) with aminolaevulinic acid photodynamic therapy (ALA-PDT) is widespread. Nonetheless, there is variation in efficacy. Therefore, this study constructed a model for predicting the short-term efficacy and recurrence of OLK after ALA-PDT. METHODS: The short-term efficacy and recurrence of ALA-PDT were calculated by statistical analysis, and the relevant influencing factors were analyzed by Logistic regression and COX regression model. Finally, prediction models for total response (TR) rate, complete response (CR) rate and recurrence in OLK patients after ALA-PDT treatment were established. Features from pathology sections were extracted using deep learning autoencoder and combined with clinical variables to improve prediction performance of the model. RESULTS: The logistic regression analysis showed that the non-homogeneous (OR: 4.911, P: 0.023) OLK and lesions with moderate to severe epithelial dysplasia (OR: 4.288, P: 0.042) had better short-term efficacy. The area under receiver operating characteristic curve (AUC) of CR, TR and recurrence predict models after the ALA-PDT treatment of OLK patients is 0.872, 0.718, and 0.564, respectively. Feature extraction revealed an association between inflammatory cell infiltration in the lamina propria and recurrence after PDT. Combining clinical variables and deep learning improved the performance of recurrence model by more than 30 %. CONCLUSIONS: ALA-PDT has excellent short-term efficacy in the management of OLK but the recurrence rate was high. Prediction model based on clinicopathological characteristics has excellent predictive effect for short-term efficacy but limited effect for recurrence. The use of deep learning and pathology images greatly improves predictive value of the models.

Association of adverse childhood experiences with poor health condition among middle-aged and elderly adults in the United States: A nationally retrospective cohort study.

BACKGROUND: The specific effects of adverse childhood experiences (ACEs) in adulthood and senectitude were less known. We aim to examine the relationship between early ACEs and overall health condition as well as specific dimensions in the middle-aged and elderly population. METHODS: In the 2019-2021 Behavioral Risk Factor Surveillance System Study, robust Poisson regression models were used to estimate the relationship between ACE exposure and current health status among adults aged 45 ≥ years. RESULTS: Of the 195,472 participants, 53.8 % were female and the mean age was 65.0 years. Compared to populations without ACE, ACE exposures were more significantly associated with depression (PR: 2.03, 95 %CI: 1.94-2.21), frequent mental health (PR: 1.85, 95 %CI: 1.74-1.97) and subject cognitive decline (PR: 1.99, 95 %CI:1.85-2.14) than with physical health (PR: 1.37, 95 %CI: 1.32-1.44), with dose-response patterns. The association with mental disorder was especially significant among the elderly population. CONCLUSION: Early ACEs are associated with adverse health outcomes that persist into later life, particularly mental disorders and cognitive decline. Poor mental health may indirectly influence associations with ACEs and cognitive decline as well as physical health. Our findings emphasize the importance of lifelong psychological screening and support for the ACE-exposed middle-aged and elderly population.

Causal association between particulate matter 2.5 and Alzheimer's disease: a Mendelian randomization study.

Background: Although epidemiological evidence implies a link between exposure to particulate matter (PM) and Alzheimer's disease (AD), establishing causality remains a complex endeavor. In the present study, we used Mendelian randomization (MR) as a robust analytical approach to explore the potential causal relationship between PM exposure and AD risk. We also explored the potential associations between PM exposure and other neurodegenerative diseases. Methods: Drawing on extensive genome-wide association studies related to PM exposure, we identified the instrumental variables linked to individual susceptibility to PM. Using summary statistics from five distinct neurodegenerative diseases, we conducted two-sample MR analyses to gauge the causal impact of PM on the risk of developing these diseases. Sensitivity analyses were undertaken to evaluate the robustness of our findings. Additionally, we executed multivariable MR (MVMR) to validate the significant causal associations identified in the two-sample MR analyses, by adjusting for potential confounding risk factors. Results: Our MR analysis identified a notable association between genetically predicted PM2.5 (PM with a diameter of 2.5 µm or less) exposure and an elevated risk of AD (odds ratio, 2.160; 95% confidence interval, 1.481 to 3.149; p < 0.001). A sensitivity analysis supported the robustness of the observed association, thus alleviating concerns related to pleiotropy. No discernible causal relationship was identified between PM and any other neurodegenerative diseases. MVMR analyses-adjusting for smoking, alcohol use, education, stroke, hearing loss, depression, and hypertension-confirmed a persistent causal relationship between PM2.5 and AD. Sensitivity analyses, including MR-Egger and weighted median analyses, also supported this causal association. Conclusion: The present MR study provides evidence to support a plausible causal connection between PM2.5 exposure and AD. The results emphasize the importance of contemplating air quality interventions as a public health strategy for reducing AD risk.

Joint association of diabetes mellitus and inflammation status with biological ageing acceleration and premature mortality.

BACKGROUND: We aimed to investigate the associations of diabetes mellitus (DM) and C-reactive protein (CRP) with biological ageing acceleration and mortality risk. METHODS: We analyzed data from 41,634 adults with CRP and DM at baseline. Subjects were categorized into high CRP (>3 mg/L) and low CRP (≤3 mg/L) groups. The cross-sectional endpoints of the study were biological ageing indicators Klemera-Doubal method BioAge acceleration (KDMAccel) and Phenotypic age acceleration (PhenoAgeAccel), and the follow-up endpoints were all-cause mortality and cardiovascular mortality. RESULTS: In adults with high CRP, compared with those without DM, PhenoAgeAccel increased by 1.66 years (95 % CI: 1.38-1.93), and 8.74 years (95 % CI: 8.25-9.22) in adults with prediabetes and DM, respectively (p for interaction <0.001). Using the CRPlow/non-DM group as a reference, adults in the CRPhigh/non-DM, CRPlow/DM, and CRPhigh/DM groups had significantly advanced biological ageing. Compared to adults without DM, low CRP, and no ageing acceleration, the multivariable-adjusted HRs (95%CIs) of all-cause and cardiovascular mortality in those with DM, CRP, and ageing acceleration were 3.22 (2.79-3.72), and 3.57 (2.81-4.54), respectively. CONCLUSIONS: These findings suggest that the joint presence of low-grade inflammation and DM might be associated with higher odds of biological ageing acceleration and premature mortality.

Decreased cobalamin sensitivity and biological aging acceleration in the general population.

BACKGROUND: The evidence on the association between cobalamin (Cbl) and aging or relevant outcomes is limited and controversial. We aimed to investigate the relationships between cobalamin intake- and function-related biomarkers and biological aging. METHODS: The study encompassed 22,812 participants aged 20 years and older from the National Health and Nutrition Examination Survey. A panel of biomarkers or algorithms was used to assess biological aging, including Klemera-Doubal Age Acceleration (KDMAccel), Phenotypic age acceleration (PhenoAgeAccel), telomere length, α-Klotho, and PhenoAge advancement. Weighted generalized linear regression analysis was used to assess the associations between cobalamin-intake biomarkers (serum cobalamin, cobalamin intake from food, cobalamin supplement use, serum methylmalonic acid [MMA], and homocysteine [Hcy]) and function-related biomarkers (functional cobalamin deficiency and cobalamin insensitivity index). RESULTS: Among the 22,812 individuals, the weighted mean (SE) age was 48.3 (0.2) years and 48.0% were males. Unexpectedly, serum and dietary cobalamin as well as serum MMA and Hcy levels were positively associated with most indicators of biological aging. Cobalamin sensitivity was assessed by the combination of binary Cbllow/high and MMAlow/high or Hcylow/high (cutoff values: 400 pg/mL for cobalamin, 250 nmol/L for MMA, and 12.1 µmol/l for Hcy) and a newly constructed cobalamin insensitivity index (based on the multiplicative term of serum cobalamin and serum MMA or Hcy). The multivariable-adjusted ß (95%CIs) of KDMAccel in the MMAlowCbllow, MMAlowCblhigh, MMAhighCbllow, and MMAhighCblhigh groups were reference, 0.27 (0.03 to 0.51), 0.85 (0.41 to 1.29), and 7.97 years (5.77 to 10.17) respectively, which were consistent for the combination of serum Hcy and cobalamin. Both cobalamin insensitivity indices were robustly associated with biological aging acceleration in a dose-response pattern (each p < 0.001). CONCLUSIONS: Decreased cobalamin sensitivity but not cobalamin insufficiency might be associated with biological aging acceleration. Further studies would improve understanding of the underlying mechanisms between decreased cobalamin sensitivity and biological aging acceleration.

Error detection for radiotherapy planning validation based on deep learning networks.

BACKGROUND: Quality assurance (QA) of patient-specific treatment plans for intensity-modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT) necessitates prior validation. However, the standard methodology exhibits deficiencies and lacks sensitivity in the analysis of positional dose distribution data, leading to difficulties in accurately identifying reasons for plan verification failure. This issue complicates and impedes the efficiency of QA tasks. PURPOSE: The primary aim of this research is to utilize deep learning algorithms for the extraction of 3D dose distribution maps and the creation of a predictive model for error classification across multiple machine models, treatment methodologies, and tumor locations. METHOD: We devised five categories of validation plans (normal, gantry error, collimator error, couch error, and dose error), conforming to tolerance limits of different accuracy levels and employing 3D dose distribution data from a sample of 94 tumor patients. A CNN model was then constructed to predict the diverse error types, with predictions compared against the gamma pass rate (GPR) standard employing distinct thresholds (3%, 3 mm; 3%, 2 mm; 2%, 2 mm) to evaluate the model's performance. Furthermore, we appraised the model's robustness by assessing its functionality across diverse accelerators. RESULTS: The accuracy, precision, recall, and F1 scores of CNN model performance were 0.907, 0.925, 0.907, and 0.908, respectively. Meanwhile, the performance on another device is 0.900, 0.918, 0.900, and 0.898. In addition, compared to the GPR method, the CNN model achieved better results in predicting different types of errors. CONCLUSION: When juxtaposed with the GPR methodology, the CNN model exhibits superior predictive capability for classification in the validation of the radiation therapy plan on different devices. By using this model, the plan validation failures can be detected more rapidly and efficiently, minimizing the time required for QA tasks and serving as a valuable adjunct to overcome the constraints of the GPR method.

Role of Bß1 overexpression in the pathogenesis of SCA12.

BACKGROUND: Spinocerebellar ataxia type 12 (SCA12) is a neurodegenerative disease caused by a CAG/CTG repeat expansion at the PPP2R2B locus. OBJECTIVE: We investigated how the CAG repeat expansion within the PPP2R2B 7B7D transcript influences the expression of Bß1 and a potential protein containing a long polyserine tract. METHODS: Transcript and protein expression were measured using quantitative PCR (qPCR) Role of Bß1 overexpression in the pathogenesis of SCA12 and Western blot, respectively, in an SK-N-MC cell model that overexpresses the full-length PPP2R2B 7B7D transcript. The apoptotic effect of a protein containing a long polyserine tract on SK-N-MC cells was evaluated using caspase 3/7 activity. RESULTS: The CAG repeat expansion increases the expression of the PPP2R2B 7B7D transcript, as well as Bß1 protein, in an SK-N-MC cell model in which the full-length PPP2R2B 7B7D transcript is overexpressed. The CAG repeat expansion within the 7B7D transcript is translated into a long polyserine tract that triggers apoptosis in SK-N-MC cells. CONCLUSIONS: The SCA12 mutation leads to overexpression of PPP2R2B Bß1 and to expression of a protein containing a long polyserine tract; both these effects potentially contribute to SCA12 pathogenesis. © 2024 International Parkinson and Movement Disorder Society.

Generation of a human induced pluripotent stem cell line JHUi004-A with heterozygous mutation for spinocerebellar ataxia type 12 using genome editing.

Spinocerebellar ataxia type 12 (SCA12) is caused by a CAG expansion mutation in PPP2R2B, a gene encoding brain-specific regulatory units of protein phosphatase 2A (PP2A); while normal alleles carry 4 to 31 triplets, the disease alleles carry 43 to 78 triplets. Here, by CRISPR/Cas9n genome editing, we have generated a human heterozygous SCA12 iPSC line with 73 triplets for the mutant allele. The heterozygous SCA12 iPSCs have normal karyotype, express pluripotency markers and are able to differentiate into the three germ layers.

The association between serum methylmalonic acid, cobalamin-related biomarkers, and long-term mortality risk in cancer survivors: a prospective cohort study.

BACKGROUND: Elevated serum methylmalonic acid (MMA), a marker of cobalamin (vitamin B12) deficiency, has been linked to cancer progression. However, the impact of MMA or cobalamin on mortality risk in cancer survivors remains unknown. OBJECTIVES: To explore the relationship between MMA, serum, dietary, and supplement of cobalamin, MMA metabolism-related genes, and poor prognosis in adult cancer survivors. METHODS: We analyzed data from 1988 cancer survivors aged ≥20 y. Patients were selected from the National Health and Nutrition Examination Survey and followed up until December 31, 2019. Weighted Cox proportional hazard regression was used to estimate hazard ratios (HRs) and the corresponding 95% confidence intervals (CIs) for mortality risk assessment. Genomic analysis identified MMA metabolism-related genes linked to early death in a 33-cancer-type cohort from The Cancer Genome Atlas. RESULTS: Among 1988 participants, 872 deaths occurred over a 10-year follow-up. Higher serum MMA levels were significantly linked to increased long-term mortality risk (tertile 3 compared with tertile 1: adjusted HR: 1.37; 95% CI: 1.11, 1.70; P-trend < 0.001). No associations were found between serum, dietary, and supplement of cobalamin and cancer survivor mortality (each P-trend > 0.143). However, MMA-associated mortality was notable in patients without deficiency. When combining cobalamin and MMA categories, multivariate-adjusted HR (95% CI) for all-cause mortality was 2.06 (95% CI: 1.60, 2.65) in participants with >250 nmol/L and cobalamin >295.1 pmol/L compared with those with MMA ≤250 nmol/L and cobalamin >295.1 pmol/L. Moreover, reduced transcriptional levels of MMA metabolism-related genes, indicating decreased mitochondrial MMA metabolism capability, are linked to an unfavorable prognosis in certain cancer types. CONCLUSIONS: Serum MMA was associated with long-term mortality risk in adult cancer survivors, which was more significant among individuals with higher levels of serum cobalamin. These findings suggest that mortality related to MMA was attributed to the insufficient flux of MMA metabolism, not cobalamin deficiency.

Artificial Intelligence-Assisted Prescription Determination for Orthokeratology Lens Fitting: From Algorithm to Clinical Practice.

OBJECTIVES: To explore the potential of artificial intelligence (AI) to assist prescription determination for orthokeratology (OK) lenses. METHODS: Artificial intelligence algorithm development followed by a real-world trial. A total of 11,502 OK lenses fitting records collected from seven clinical environments covering major brands. Records were randomly divided in a three-way data split. Cross-validation was used to identify the most accurate algorithm, followed by an evaluation using an independent test data set. An online AI-assisted system was implemented and assessed in a real-world trial involving four junior and three senior clinicians. RESULTS: The primary outcome measure was the algorithm's accuracy (ACC). The ACC of the best performance of algorithms to predict the targeted reduction amplitude, lens diameter, and alignment curve of the prescription was 0.80, 0.82, and 0.83, respectively. With the assistance of the AI system, the number of trials required to determine the final prescription significantly decreased for six of the seven participating clinicians (all P <0.01). This reduction was more significant among junior clinicians compared with consultants (0.76±0.60 vs. 0.32±0.60, P <0.001). Junior clinicians achieved clinical outcomes comparable to their seniors, as 93.96% (140/149) and 94.44% (119/126), respectively, of the eyes fitted achieved unaided visual acuity no worse than 0.8 ( P =0.864). CONCLUSIONS: AI can improve prescription efficiency and reduce discrepancies in clinical outcomes among clinicians with differing levels of experience. Embedment of AI in practice should ultimately help lessen the medical burden and improve service quality for myopia boom emerging worldwide.