Repetitive transcranial magnetic stimulation in Alzheimer's disease: effects on neural and synaptic rehabilitation.

Alzheimer's disease is a neurodegenerative disease resulting from deficits in synaptic transmission and homeostasis. The Alzheimer's disease brain tends to be hyperexcitable and hypersynchronized, thereby causing neurodegeneration and ultimately disrupting the operational abilities in daily life, leaving patients incapacitated. Repetitive transcranial magnetic stimulation is a cost-effective, neuro-modulatory technique used for multiple neurological conditions. Over the past two decades, it has been widely used to predict cognitive decline; identify pathophysiological markers; promote neuroplasticity; and assess brain excitability, plasticity, and connectivity. It has also been applied to patients with dementia, because it can yield facilitatory effects on cognition and promote brain recovery after a neurological insult. However, its therapeutic effectiveness at the molecular and synaptic levels has not been elucidated because of a limited number of studies. This study aimed to characterize the neurobiological changes following repetitive transcranial magnetic stimulation treatment, evaluate its effects on synaptic plasticity, and identify the associated mechanisms. This review essentially focuses on changes in the pathology, amyloidogenesis, and clearance pathways, given that amyloid deposition is a major hypothesis in the pathogenesis of Alzheimer's disease. Apoptotic mechanisms associated with repetitive transcranial magnetic stimulation procedures and different pathways mediating gene transcription, which are closely related to the neural regeneration process, are also highlighted. Finally, we discuss the outcomes of animal studies in which neuroplasticity is modulated and assessed at the structural and functional levels by using repetitive transcranial magnetic stimulation, with the aim to highlight future directions for better clinical translations.

A Study on the Effect of Executive Control Network Functional Connection on the Therapeutic Efficacy of Repetitive Transcranial Magnetic Stimulation in Alzheimer's Disease.

Background: Alzheimer's disease (AD) is a neurodegenerative disease characterized by brain network dysfunction. Few studies have investigated whether the functional connections between executive control networks (ECN) and other brain regions can predict the therapeutic effect of repetitive transcranial magnetic stimulation (rTMS). Objective: The purpose of this study is to examine the relationship between the functional connectivity (FC) within ECN networks and the efficacy of rTMS. Methods: We recruited AD patients for rTMS treatment. We established an ECN using baseline period fMRI data and conducted an analysis of the ECN's FC throughout the brain. Concurrently, the support vector regression (SVR) method was employed to project post-rTMS cognitive scores, utilizing the connectional attributes of the ECN as predictive markers. Results: The average age of the patients was 66.86±8.44 years, with 8 males and 13 females. Significant improvement on most cognitive measures. We use ECN connectivity and brain region functions in baseline patients as features for SVR model training and fitting. The SVR model could demonstrate significant predictability for changes in Montreal Cognitive Assessment scores among AD patients after rTMS treatment. The brain regions that contributed most to the prediction of the model (the top 10% of weights) were located in the medial temporal lobe, middle temporal gyrus, frontal lobe, parietal lobe and occipital lobe. Conclusions: The stronger the antagonism between ECN and parieto-occipital lobe function, the better the prediction of cognitive improvement; the stronger the synergy between ECN and fronto-temporal lobe function, the better the prediction of cognitive improvement.

Improved U-net network asphalt pavement crack detection method.

Road crack detection is one of the important parts of road safety detection. Aiming at the problems such as weak segmentation effect of basic U-Net on pavement crack, insufficient precision of crack contour segmentation, difficult to identify narrow crack and low segmentation accuracy, this paper proposes an improved U-net network pavement crack segmentation method. VGG16 and Up_Conv (Upsampling Convolution) modules are introduced as backbone network and feature enhancement network respectively, and the more abstract features in the image are extracted by using the Block depth separable convolution blocks, and the multi-scale features are captured and enhanced by higher level semantic information to improve the recognition accuracy of narrow cracks in the road surface. The improved network embedded the Ca(Channel Attention) attention mechanism in U-net's jump connection to enhance the crack portion to suppress background noise. At the same time, DG_Conv(Depthwise GSConv Convolution) module and UnetUp(Unet Upsampling) module are added in the decoding part to extract richer features through more convolutional layers in the network, so that the model pays more attention to the detailed part of the crack, so the segmentation accuracy can be improved. In order to verify the model's ability to detect cracks in complex backgrounds, experiments were carried out on CFD and Deepcrack datasets. The experimental results show that compared with the traditional U-net network F1-score and mIoU have increased by 13.6% and 9.9% respectively. Superior to advanced models such as U-net, Segnet and Linknet in accuracy and generalization ability, the improved model provides a new method for asphalt pavement crack detection. The model is more conducive to practical application and ground deployment, and can be applied in road maintenance projects.

Efficacy and safety of cortical bone trajectory screws versus pedicle screws in lumbar fusion: a systematic review and meta-analysis.

OBJECTIVE: A systematic review and meta-analysis was conducted to compare the efficacy and safety of cortical bone trajectory screws and traditional pedicle screws in lumbar fusion. METHODS: Randomized controlled studies and cohort studies on CBT versus pedicle screws in lumbar fusion were searched in CBM, CNKI, Wanfang, VIP, PubMed, Cochrane Library and Web of Science databases. The search period spanned from the establishment of the databases to December 2023. The Cochrane bias risk assessment tool and Newcastle-Ottawa scale were applied to assess the quality of the literature included. Clinical and imaging data as well as surgical outcomes, recovery and postoperative complications were extracted from the relevant literature. RESULTS: A total of 6 randomized controlled trials and 26 cohort studies were included after screening by inclusion and exclusion criteria with a total of 2478 patients. The meta-analysis demonstrated significant discrepancies between the CBT and TPS groups in JOA score at 3 and 6 months, and final follow-up. Moreover, the TPS group exhibited a higher ODI at final follow-up, a greater VAS for low back pain at both 1 week and final follow-up, as well as a higher VAS for leg pain at 1 month. Differences were also noted in surgical and recovery outcomes. However, there was no significant difference between the two groups in postoperative complications. CONCLUSIONS: CBT and TPS have analogous safety profiles when applied to lumbar fusion, but the clinical efficacy of CBT is superior to that of TPS to some extent, and the procedure is less invasive with faster recovery.

An L-shaped relationship between dietary vitamin K and atherosclerotic cardiovascular disease.

BACKGROUND AND AIMS: Few studies link vitamin K intake with incident atherosclerotic cardiovascular disease (ASCVD), and the specific mechanism remains uncertain. We aimed to evaluate the relationship between dietary vitamin K and ASCVD. METHODS: This study used cross-sectional data from people over 20 years old who took part in the National Health and Nutrition Examination Survey (NHANES) between 2013 and 2018. Vitamin K intake was assessed using a 24-h dietary review. The Patient Medical Conditions Questionnaire was used to assess ASCVD. The stability of the outcomes was evaluated using cubic spline models with restricted parameters and logistic regression, while subgroup analyses were also performed. RESULTS: There were 14,465 participants, with 9.78% (1415/14,465) who diagnosed with ASCVD. Compared with individuals with lower vitamin K intake Q1 (≤39.0 ug/day), the adjusted OR values for dietary vitamin K intake and ASCVD in Q2 (39.1-70.8 ug/day), Q3 (70.9-131.0 mg/day), and Q4 (≥131.1 ug/day) were 0.88 (95% CI: 0.74-1.04, p = 0.134), 0.77(95% CI: 0.65-0.93, p = 0.005), and 0.78 (95% CI: 0.65-0.95, p = 0.013), respectively. The association between dietary vitamin K intake and ASCVD showed an L-shaped curve (nonlinear, p = 0.006). The OR for ASCVD in participants with vitamin K intake <127.1ug/day was 0.996 (95% CI: 0.993-0.998, p = 0.002). CONCLUSIONS: The relationship between dietary vitamin K intake and ASCVD was L-shaped curve in US adults, the inflection point was roughly 127.1 ug/day.

Abnormal EEG microstates in Alzheimer's disease: predictors of ß-amyloid deposition degree and disease classification.

Electroencephalography (EEG) microstates are used to study cognitive processes and brain disease-related changes. However, dysfunctional patterns of microstate dynamics in Alzheimer's disease (AD) remain uncertain. To investigate microstate changes in AD using EEG and assess their association with cognitive function and pathological changes in cerebrospinal fluid (CSF). We enrolled 56 patients with AD and 38 age- and sex-matched healthy controls (HC). All participants underwent various neuropsychological assessments and resting-state EEG recordings. Patients with AD also underwent CSF examinations to assess biomarkers related to the disease. Stepwise regression was used to analyze the relationship between changes in microstate patterns and CSF biomarkers. Receiver operating characteristics analysis was used to assess the potential of these microstate patterns as diagnostic predictors for AD. Compared with HC, patients with AD exhibited longer durations of microstates C and D, along with a decreased occurrence of microstate B. These microstate pattern changes were associated with Stroop Color Word Test and Activities of Daily Living scale scores (all P < 0.05). Mean duration, occurrences of microstate B, and mean occurrence were correlated with CSF Aß 1-42 levels, while duration of microstate C was correlated with CSF Aß 1-40 levels in AD (all P < 0.05). EEG microstates are used to predict AD classification with moderate accuracy. Changes in EEG microstate patterns in patients with AD correlate with cognition and disease severity, relate to Aß deposition, and may be useful predictors for disease classification.

Evaluation of systemic medications associated with diabetic retinopathy: a nested case-control study from the UK Biobank.

AIMS: This study aims to investigate the associations between commonly used systemic medications and diabetic retinopathy (DR). METHODS: Individuals with linked primary care prescription data from the UK Biobank were included. Cases were defined as individuals with a Hospital Episode Statistics-coded or primary care recorded diagnosis of DR or self-reported DR. Controls were matched for age, sex, glycosylated haemoglobin, duration of diabetes mellitus (DM), hypertension status and cardiovascular disease status. ORs and 95% CIs were calculated using conditional univariate and multivariable logistic regression models. RESULTS: A total of 3377 case subjects with DR were included in the study and matched with 3377 control subjects. In multivariable logistic regression, increased odds of incident DR were observed for exposure to short-acting insulins (OR 1.63; 95% CI 1.22 to 2.18), medium-acting insulins (OR 2.10; 95% CI 1.60 to 2.75), sulfonylureas (OR 1.30; 95% CI 1.16 to 1.46). Instead, the use of fibrates (OR 0.71; 95% CI 0.53 to 0.94) and Cox-2 inhibitors (OR 0.68; 95% CI 0.58 to 0.79) was associated with decreased odds of incident DR. Dose-response relationships were observed for all five drug categories (all p<0.05). CONCLUSIONS: This study comprehensively investigated the associations between systemic medication use and DR and found significant associations between the use of short-acting insulins, medium-acting insulins and sulfonylureas with increased odds of incident DR. In contrast, fibrates and Cox-2 inhibitors were associated with decreased odds of incident DR. These findings may provide valuable insights into DM medication management and serve as a reference for the prevention of DR in patients with DM.

The ameliorative mechanism of Lactiplantibacillus plantarum NJAU-01 against D-galactose induced oxidative stress: a hepatic proteomics and gut microbiota analysis.

Probiotic intervention is an effective strategy to alleviate oxidative stress-related diseases. Our previous studies found that Lactiplantibacillus plantarum NJAU-01 (NJAU-01) exhibited antioxidant effects in a D-galactose (D-gal)-induced aging mouse model. However, the underlying mechanism remains to be unveiled. This study was aimed to investigate the ameliorative effect and mechanism of NJAU-01 against oxidative stress induced by D-gal. The results showed that NJAU-01 could reverse the tendency of a slow body weight gain induced by D-gal. NJAU-01 relieved hepatic oxidative stress via increasing the hepatic total antioxidant capacity and antioxidant enzyme activities including superoxide dismutase (SOD), glutathione peroxidase (GSH-Px) and catalase (CAT). Moreover, the malondialdehyde (MDA) level was reversed after NJAU-01 supplementation. The proteomic results showed that there were 201 differentially expressed proteins (DEPs) between NJAU-01 and D-gal groups. NJAU-01 regulated the expressions of glutathione S-transferase Mu 5 (Gstm5), glutathione S-transferase P2 (Gstp2) and NADH dehydrogenase 1α subcomplex subunit 7 (Ndufa7) related to oxidative stress, and autophagy protein 5 (Atg5) and plasma alpha-L-fucosidase (Fuca2) involved in autophagy, etc. 16S rDNA sequencing results showed that NJAU-01 supplementation could regulate the gut microbiota dysbiosis induced by D-gal via increasing the relative abundances of the phylum Firmicutes and the genus Lactobacillus and reducing the relative abundances of the phylum Bacteroidetes and the genera Lachnospiraceae_NK4A136_group as well as Prevotellaceae_UCG-001, etc.. Spearman correlation analysis results showed that the altered gut microbiota composition had a significant correlation with antioxidant enzyme activities and the DEPs related to oxidative stress. Overall, NJAU-01 alleviated hepatic oxidative stress induced by D-gal via manipulating the gut microbiota composition and hepatic protein expression profile.

Greenness, air pollution, and mortality risk: a retrospective cohort study of patients with lung cancer in China.

The association between long-term exposure to air pollution and mortality from lung cancer has been established, yet evaluations of the potential mitigating effects of greenness on this impact are scarce. We conducted a cohort study in Pingyi County. A two-level Cox proportional hazards regression model was used to examine the associations among long-term exposure to air pollution, residential greenness, and lung cancer mortality. Among the examined pollutants, nitrogen dioxide exhibited the most significant adverse effects and highest risk of lung cancer mortality, with hazard ratio (HR) = 2.783 (95% confidence interval [CI]: 1.885-4.107) for all-cause mortality, HR = 2.492 (95%CI: 1.659-3.741) for tumour-related mortality, and HR = 2.431 (95%CI: 1.606-3.678) for lung cancer mortality. Higher greenness values were associated with a reduced risk of lung cancer mortality. These findings suggest the importance of implementing strategies for increasing greenness to reduce the health impacts of air pollution.

TAK-242 inhibits glioblastoma invasion, migration, and proneural-mesenchymal transition by inhibiting TLR4 signaling.

Resatorvid (TAK-242), a small-molecule inhibitor of Toll-like receptor 4 (TLR4), has the ability to cross the blood-brain barrier (BBB). In this study, we explored the role of TAK-242 on glioblastoma (GBM) invasion, migration, and proneural-mesenchymal transition (PMT). RNA sequencing (RNA-Seq) data and full clinical information of glioma patients were downloaded from the Chinese Glioma Genome Atlas (CGGA) and the Cancer Genome Atlas (TCGA) cohorts and then analyzed using R language; patients were grouped based on proneural (PN) and mesenchymal (MES) subtypes. Bioinformatics analysis was used to detect the difference in survival and TLR4-pathway expression between these groups. Cell viability assay, wound-healing test, and transwell assay, as well as an intracranial xenotransplantation mice model, were used to assess the functional role of TAK-242 in GBM in vitro and in vivo. RNA-Seq, Western blot, and immunofluorescence were employed to investigate the possible mechanism. TLR4 expression in GBM was significantly higher than in normal brain tissue and upregulated the expression of MES marker genes. Moreover, TAK-242 inhibited GBM progression in vitro and in vivo via linking with PMT, which could be a novel treatment strategy for inhibiting GBM recurrence.

Comparing the pharmacological effects of the prepared folium of Epimedium brevicornu Maxim. and Epimedium sagittatum Maxim. on kidney-Yang deficiency syndrome and liver injury complications.

Yinyanghuo, a famous herb, includes the folium of Epimedium brevicornu Maxim. and Epimedium sagittatum Maxim. It is believed that their processed products, the prepared slices of the folium of Epimedium brevicornu Maxim. (PFEB) and Epimedium sagittatum Maxim. (PFES) have greater efficacy in tonifying kidney Yang to treat kidney-Yang deficiency syndrome (KDS). However, there are few studies comparing the pharmacological effects of PFEB and PFES, and the underlying mechanisms. This study compared their effects on improving hypothalamic-pituitary-adrenal (HPA) axis, immune system and sexual characteristic, as well as repairing liver injury complications in the KDS model mice. Additionally, the mechanisms of the effects relevance to their main components were explored. It was found that PFEB was more effective than PFES in increasing cAMP/cGMP ratio, SOD activity, CRH and ACTH levels, eNOS and testosterone levels, splenic lymphocytes proliferation, while in decreasing MDA content, atrophy of spleen and thymus, splenic lymphocytes apoptosis, and PDE5 level. PFES showed stronger protection than PFEB in decreasing triglyceride and hepatic lipid. The contents of baohuoside I and epimedin A, B were much higher in PFEB, while Epimedin C, Icariin, 2-O″-rhamnosylicaridide II were higher in PFES. Consequently, PFEB exhibits superior efficacy over PFES in tonifying the kidney-Yang by improving the neuroendocrine-immune network, including HPA axis, immune systems, and corpus cavernosum. However, PFES has better recovery effect on mild hepatic lipid caused by KDS. The efficacy difference between PFEB and PFES in kidney-Yang and liver may be attributed to the content variations of baohuoside I.

Dual-Mode Hydrogels with Structural and Fluorescent Colors toward Multistage Secure Information Encryption.

Constructing an anti-counterfeiting material with non-interference dual optical modes is an effective way to improve information security. However, it remains challenging to achieve multistage secure information encryption due to the limited stimulus responsiveness and color tunability of the current dual-mode materials. Herein, a dual-mode hydrogel with both independently tunable structural and fluorescent colors toward multistage information encryption, is reported. In this hydrogel system, the rigid lamellar structure of poly(dodecylglyceryl itaconate) (pDGI) formed by shear flow-induced self-assembly provides the restricted domains wherein monomers undergo polymerization to form a hydrogel network, producing structural color. The introduction of fluorescent monomer 6-acrylamidopicolinate (6APA) as a complexation site provides the possibility of fluorescent color formation. The hydrogel's angle-dependent structural color can be controlled by adjusting the crosslinking density and water content. Additionally, the fluorescence color can be modulated by adjusting the ratio of lanthanide ions. Information of dual-mode can be displayed separately in different channels and synergistically overlayed to read the ultimate message. Thus, a multistage information encryption system based on this hydrogel is devised through the programed decryption process. This strategy holds tremendous potential as a platform for encrypting and safeguarding valuable and authentic information in the field of anti-counterfeiting.

Deep-learning enhanced high-quality imaging in metalens-integrated camera.

Because of their ultra-light, ultra-thin, and flexible design, metalenses exhibit significant potential in the development of highly integrated cameras. However, the performances of metalens-integrated camera are constrained by their fixed architectures. Here we proposed a high-quality imaging method based on deep learning to overcome this constraint. We employed a multi-scale convolutional neural network (MSCNN) to train an extensive pair of high-quality and low-quality images obtained from a convolutional imaging model. Through our method, the imaging resolution, contrast, and distortion have all been improved, resulting in a noticeable overall image quality with SSIM over 0.9 and an improvement in PSNR over 3 dB. Our approach enables cameras to combine the advantages of high integration with enhanced imaging performances, revealing tremendous potential for a future groundbreaking imaging technology.

Assessment of OCT-Based Macular Curvature and Its Relationship with Macular Microvasculature in Children with Anisomyopia.

INTRODUCTION: To evaluate the intraocular differences in optical coherence tomography (OCT)-based macular curvature index (MCI) among children with anisomyopia and to investigate the relationship between MCI and the macular microvasculature. METHODS: Fifty-two schoolchildren with anisometropia > 2.00 D were enrolled and underwent comprehensive examinations including cycloplegic refraction, axial length (AL), and swept source OCT/OCT angiography. OCT-based MCIs were determined from horizontal and vertical B-scans by a customized curve fitting model in MATLAB R2022 at 1-mm-, 3-mm-, and 6-mm-diameter circles at fovea. Characteristics and topographic variation of MCI was analyzed, and the relationships with microvascularity and its associated factors were investigated. RESULTS: MCI achieved high reliability and repeatability. There were overall larger MCIs in the more myopic eyes than the less myopic eyes in 1-mm-, 3-mm-, and 6-mm-diameter circles at fovea (all p < 0.001). For the topographic variation, horizontal MCI was significantly greater than vertical MCI (all p < 0.001), and was the largest in 6-mm circle, followed by 3-mm and 1-mm circles. Stronger correlation of horizontal MCI with myopic severity than vertical MCI was found. Partial Pearson's correlation found MCI was negatively associated with deep capillary plexus (DCP) vessel density (p = 0.016). Eyes with a higher MCI in a 6-mm circle were more likely to have longer AL (p < 0.001), lower DCP vessel density (p = 0.037), and thinner choroidal thickness (ChT) (p = 0.045). CONCLUSION: Larger MCI was found in the more myopic eyes of children with anisomyopia and was significantly associated with smaller DCP density, suggesting that MCI was an important indicator of myopia-related retinal microvascularity change, and it could be a valuable metric for myopia assessment in children.

Computer vision models enable mixed linear modeling to predict arbuscular mycorrhizal fungal colonization using fungal morphology.

The presence of Arbuscular Mycorrhizal Fungi (AMF) in vascular land plant roots is one of the most ancient of symbioses supporting nitrogen and phosphorus exchange for photosynthetically derived carbon. Here we provide a multi-scale modeling approach to predict AMF colonization of a worldwide crop from a Recombinant Inbred Line (RIL) population derived from Sorghum bicolor and S. propinquum. The high-throughput phenotyping methods of fungal structures here rely on a Mask Region-based Convolutional Neural Network (Mask R-CNN) in computer vision for pixel-wise fungal structure segmentations and mixed linear models to explore the relations of AMF colonization, root niche, and fungal structure allocation. Models proposed capture over 95% of the variation in AMF colonization as a function of root niche and relative abundance of fungal structures in each plant. Arbuscule allocation is a significant predictor of AMF colonization among sibling plants. Arbuscules and extraradical hyphae implicated in nutrient exchange predict highest AMF colonization in the top root section. Our work demonstrates that deep learning can be used by the community for the high-throughput phenotyping of AMF in plant roots. Mixed linear modeling provides a framework for testing hypotheses about AMF colonization phenotypes as a function of root niche and fungal structure allocations.

MdARF3 switches the lateral root elongation to regulate dwarfing in apple plants.

Apple rootstock dwarfing and dense planting are common practices in apple farming. However, the dwarfing mechanisms are not understood. In our study, the expression of MdARF3 in the root system of dwarfing rootstock 'M9' was lower than in the vigorous rootstock from Malus micromalus due to the deletion of the WUSATAg element in the promoter of the 'M9' genotype. Notably, this deletion variation was significantly associated with dwarfing rootstocks. Subsequently, transgenic tobacco (Nicotiana tabacum) cv. Xanthi was generated with the ARF3 promoter from 'M9' and M. micromalus genotypes. The transgenic apple with 35S::MdARF3 was also obtained. The transgenic tobacco and apple with the highly expressed ARF3 had a longer root system and a higher plant height phenotype. Furthermore, the yeast one-hybrid, luciferase, electrophoretic mobility shift assays, and Chip-qPCR identified MdWOX4-1 in apples that interacted with the pMm-ARF3 promoter but not the pM9-ARF3 promoter. Notably, MdWOX4-1 significantly increased the transcriptional activity of MdARF3 and MdLBD16-2. However, MdARF3 significantly decreased the transcriptional activity of MdLBD16-2. Further analysis revealed that MdARF3 and MdLBD16-2 were temporally expressed during different stages of lateral root development. pMdLBD16-2 was mainly expressed during the early stage of lateral root development, which promoted lateral root production. On the contrary, pMmARF3 was expressed during the late stage of lateral root development to promote elongation. The findings in our study will shed light on the genetic causes of apple plant dwarfism and provide strategies for molecular breeding of dwarfing apple rootstocks.

Antitumor effects of polydopamine coated hydroxyapatite nanoparticles and its mechanism: Mitochondria-targeted ROS and calcium channels.

Nano hydroxyapatite (nHA) has been acknowledged for its inhibition efficiency on tumor cells and its excellent biocompatibility for normal tissue and cells. However, the low inhibitory efficiency of tumor cells and the ambiguous inhibitory mechanism limited its further application. In this work, four kinds of nHA with different sizes was prepared, and the one with the highest inhibition efficiency on 4T1 cells was screened as a substrate for developing the nanoparticles coated with polydopamine (PDA) coating, which was named nHA-PDA. Both in vivo and in vitro experiments were employed, and the results showed significantly higher inhibitory activity against 4T1 cells and 4T1-bared tumors by nHA-PDA. Further investigation revealed that the oxidative stress induced by PDA results in a large Reactive Oxygen Species (ROS) accumulation, thus triggering the mitochondria-dependent apoptosis pathway ROS-JNK/MAPK and inducing the cascade reaction of inhibiting the anti-apoptosis protein-Bcl-2 expression and activating the expression of the critical genes in apoptosis signaling pathway (caspase 3 and caspase 9). Besides, the significant increase of intracellular [Ca2+] may also be an essential reason for the damage of mitochondria, eventually leading to apoptosis.

Risk prediction model based on machine learning for predicting miscarriage among pregnant patients with immune abnormalities.

Introduction: It is known that patients with immune-abnormal co-pregnancies are at a higher risk of adverse pregnancy outcomes. Traditional pregnancy risk management systems have poor prediction abilities for adverse pregnancy outcomes in such patients, with many limitations in clinical application. In this study, we will use machine learning to screen high-risk factors for miscarriage and develop a miscarriage risk prediction model for patients with immune-abnormal pregnancies. This model aims to provide an adjunctive tool for the clinical identification of patients at high risk of miscarriage and to allow for active intervention to reduce adverse pregnancy outcomes. Methods: Patients with immune-abnormal pregnancies attending Sichuan Provincial People's Hospital were collected through electronic medical records (EMR). The data were divided into a training set and a test set in an 8:2 ratio. Comparisons were made to evaluate the performance of traditional pregnancy risk assessment tools for clinical applications. This analysis involved assessing the cost-benefit of clinical treatment, evaluating the model's performance, and determining its economic value. Data sampling methods, feature screening, and machine learning algorithms were utilized to develop predictive models. These models were internally validated using 10-fold cross-validation for the training set and externally validated using bootstrapping for the test set. Model performance was assessed by the area under the characteristic curve (AUC). Based on the best parameters, a predictive model for miscarriage risk was developed, and the SHapley additive expansion (SHAP) method was used to assess the best model feature contribution. Results: A total of 565 patients were included in this study on machine learning-based models for predicting the risk of miscarriage in patients with immune-abnormal pregnancies. Twenty-eight risk warning models were developed, and the predictive model constructed using XGBoost demonstrated the best performance with an AUC of 0.9209. The SHAP analysis of the best model highlighted the total number of medications, as well as the use of aspirin and low molecular weight heparin, as significant influencing factors. The implementation of the pregnancy risk scoring rules resulted in accuracy, precision, and F1 scores of 0.3009, 0.1663, and 0.2852, respectively. The economic evaluation showed a saving of ¥7,485,865.7 due to the model. Conclusion: The predictive model developed in this study performed well in estimating the risk of miscarriage in patients with immune-abnormal pregnancies. The findings of the model interpretation identified the total number of medications and the use of other medications during pregnancy as key factors in the early warning model for miscarriage risk. This provides an important basis for early risk assessment and intervention in immune-abnormal pregnancies. The predictive model developed in this study demonstrated better risk prediction performance than the Pregnancy Risk Management System (PRMS) and also demonstrated economic value. Therefore, miscarriage risk prediction in patients with immune-abnormal pregnancies may be the most cost-effective management method.

Construction and validation of a deep learning prognostic model based on digital pathology images of stage III colorectal cancer.

BACKGROUND: TNM staging is the main reference standard for prognostic prediction of colorectal cancer (CRC), but the prognosis heterogeneity of patients with the same stage is still large. This study aimed to classify the tumor microenvironment of patients with stage III CRC and quantify the classified tumor tissues based on deep learning to explore the prognostic value of the developed tumor risk signature (TRS). METHODS: A tissue classification model was developed to identify nine tissues (adipose, background, debris, lymphocytes, mucus, smooth muscle, normal mucosa, stroma, and tumor) in whole-slide images (WSIs) of stage III CRC patients. This model was used to extract tumor tissues from WSIs of 265 stage III CRC patients from The Cancer Genome Atlas and 70 stage III CRC patients from the Sixth Affiliated Hospital of Sun Yat-sen University. We used three different deep learning models for tumor feature extraction and applied a Cox model to establish the TRS. Survival analysis was conducted to explore the prognostic performance of TRS. RESULTS: The tissue classification model achieved 94.4 % accuracy in identifying nine tissue types. The TRS showed a Harrell's concordance index of 0.736, 0.716, and 0.711 in the internal training, internal validation, and external validation sets. Survival analysis showed that TRS had significant predictive ability (hazard ratio: 3.632, p = 0.03) for prognostic prediction. CONCLUSION: The TRS is an independent and significant prognostic factor for PFS of stage III CRC patients and it contributes to risk stratification of patients with different clinical stages.

A novel protein CYTB-187AA encoded by the mitochondrial gene CYTB modulates mammalian early development.

The mitochondrial genome transcribes 13 mRNAs coding for well-known proteins essential for oxidative phosphorylation. We demonstrate here that cytochrome b (CYTB), the only mitochondrial-DNA-encoded transcript among complex III, also encodes an unrecognized 187-amino-acid-long protein, CYTB-187AA, using the standard genetic code of cytosolic ribosomes rather than the mitochondrial genetic code. After validating the existence of this mtDNA-encoded protein arising from cytosolic translation (mPACT) using mass spectrometry and antibodies, we show that CYTB-187AA is mainly localized in the mitochondrial matrix and promotes the pluripotent state in primed-to-naive transition by interacting with solute carrier family 25 member 3 (SLC25A3) to modulate ATP production. We further generated a transgenic knockin mouse model of CYTB-187AA silencing and found that reduction of CYTB-187AA impairs females' fertility by decreasing the number of ovarian follicles. For the first time, we uncovered the novel mPACT pattern of a mitochondrial mRNA and demonstrated the physiological function of this 14th protein encoded by mtDNA.