Methylation entropy landscape of Chinese long-lived individuals reveals lower epigenetic noise related to human healthy aging.

The transition from ordered to noisy is a significant epigenetic signature of aging and age-related disease. As a paradigm of healthy human aging and longevity, long-lived individuals (LLI, >90 years old) may possess characteristic strategies in coping with the disordered epigenetic regulation. In this study, we constructed high-resolution blood epigenetic noise landscapes for this cohort by a methylation entropy (ME) method using whole genome bisulfite sequencing (WGBS). Although a universal increase in global ME occurred with chronological age in general control samples, this trend was suppressed in LLIs. Importantly, we identified 38,923 genomic regions with LLI-specific lower ME (LLI-specific lower entropy regions, for short, LLI-specific LERs). These regions were overrepresented in promoters, which likely function in transcriptional noise suppression. Genes associated with LLI-specific LERs have a considerable impact on SNP-based heritability of some aging-related disorders (e.g., asthma and stroke). Furthermore, neutrophil was identified as the primary cell type sustaining LLI-specific LERs. Our results highlight the stability of epigenetic order in promoters of genes involved with aging and age-related disorders within LLI epigenomes. This unique epigenetic feature reveals a previously unknown role of epigenetic order maintenance in specific genomic regions of LLIs, which helps open a new avenue on the epigenetic regulation mechanism in human healthy aging and longevity.

High-dose dual therapy versus bismuth-containing quadruple therapy for the eradication of Helicobacter pylori: A systematic review and meta-analysis.

OBJECTIVE: To update evidence-based data comparing the efficacy and safety of high-dose dual therapy (HDDT) and bismuth-containing quadruple therapy (BQT) in eradicating Helicobacter pylori infection through meta-analysis. METHODS: Multiple databases were systematically searched for randomized controlled trials (RCTs) published up to May 18, 2023. Dichotomous data were evaluated using risk ratio (RR) and 95% confidence interval (CI). Subgroup analysis, sensitivity analysis, risk of bias assessment, and quality of evidence evaluation were performed. RESULTS: Twenty RCTs containing 7891 subjects were included in the analysis. There was no statistically significant difference in H. pylori eradication rate between HDDT and BQT in the intention-to-treat (ITT) analysis (86.31% vs 84.88%; RR 1.02, 95% CI 1.00-1.04, P = 0.12). In the per-protocol (PP) analysis, the eradication rates for HDDT and BQT were 90.27% and 89.94%, respectively (RR 1.01, 95% CI 0.99-1.03, P = 0.44). Adverse events were significantly lower with HDDT than with BQT (RR 0.44, 95% CI 0.38-0.51, P < 0.00001). Patient adherence was significantly different between the two groups (RR 1.01, 95% CI 1.00-1.03, P = 0.02). Subgroup analysis based on antibiotic combinations within the BQT group showed a significantly higher eradication rate for HDDT than for BQT only when BQT used amoxicillin combined with clarithromycin (P = 0.0009). CONCLUSIONS: HDDT showed comparable efficacy with BQT for H. pylori eradication, with fewer adverse effects and higher compliance. Due to regional differences, antibiotic resistance rates, and combined BQT antibiotics, more studies are needed for further validation and optimization of HDDT.

Development strategies and application of antimicrobial peptides as future alternatives to in-feed antibiotics.

The use of in-feed antibiotics has been widely restricted due to the significant environmental pollution and food safety concerns they have caused. Antimicrobial peptides (AMPs) have attracted widespread attention as potential future alternatives to in-feed antibiotics owing to their demonstrated antimicrobial activity and environment friendly characteristics. However, the challenges of weak bioactivity, immature stability, and low production yields of natural AMPs impede practical application in the feed industry. To address these problems, efforts have been made to develop strategies for approaching the AMPs with enhanced properties. Herein, we summarize approaches to improving the properties of AMPs as potential alternatives to in-feed antibiotics, mainly including optimization of structural parameters, sequence modification, selection of microbial hosts, fusion expression, and industrially fermentation control. Additionally, the potential for application of AMPs in animal husbandry is discussed. This comprehensive review lays a strong theoretical foundation for the development of in-feed AMPs to achieve the public health globally.

Real-Time Monitoring of Tyrosine Hydroxylase Activity with a Ratiometric Fluorescent Probe.

Parkinson's disease (PD) represents the second most widespread neurodegenerative disease, and early monitoring and diagnosis are urgent at present. Tyrosine hydroxylase (TH) is a key enzyme for producing dopamine, the levels of which can serve as an indicator for assessing the severity and progression of PD. This renders the specific detection and visualization of TH a strategically vital way to meet the above demands. However, a fluorescent probe for TH monitoring is still missing. Herein, three rationally designed wash-free ratiometric fluorescent probes were proposed. Among them, TH-1 exhibited ideal photophysical properties and specific dual-channel bioimaging of TH activity in SH-SY5Y nerve cells. Moreover, the probe allowed for in vivo imaging of TH activity in zebrafish brain and living striatal slices of mice. Overall, the ratiometric fluorescent probe TH-1 could serve as a potential tool for real-time monitoring of PD in complex biosystems.

Eukaryotic translation initiation factor EIF4G1 p.Ser637Cys mutation in a family with Parkinson's disease with antecedent essential tremor.

Essential tremor (ET) and Parkinson's disease (PD) are common chronic movement disorders that can cause a substantial degree of disability. However, the etiology underlying these two conditions remains poorly understood. In the present study, Whole-exome sequencing of peripheral blood samples from the proband and Sanger sequencing of the other 18 family members, and pedigree analysis of four generations of 29 individuals with both ET and PD in a nonconsanguineous Chinese family were performed. Specifically, family members who had available medical information, including historical documentation and physical examination records, were included. A novel c.1909A>T (p.Ser637Cys) missense mutation was identified in the eukaryotic translation initiation factor 4γ1 (EIF4G1) gene as the candidate likely responsible for both conditions. In total, 9 family members exhibited tremor of the bilateral upper limbs and/or head starting from ages of ≥40 years, 3 of whom began showing evidence of PD in their 70s. Eukaryotic initiation factor 4 (eIF4)G1, a component of the translation initiation complex eIF4F, serves as a scaffold protein that interacts with many initiation factors and then binds to the 40S ribosomal subunit. The EIF4G1 (p.Ser637Cys) might inhibit the recruitment of the mRNA to the ribosome. In conclusion, the results from the present study suggested that EIF4G1 may be responsible for the hereditary PD with 'antecedent ET' reported in the family assessed.

Predicting the error magnitude in patient-specific QA during radiotherapy based on ResNet.

BACKGROUND: The error magnitude is closely related to patient-specific dosimetry and plays an important role in evaluating the delivery of the radiotherapy plan in QA. No previous study has investigated the feasibility of deep learning to predict error magnitude. OBJECTIVE: The purpose of this study was to predict the error magnitude of different delivery error types in radiotherapy based on ResNet. METHODS: A total of 34 chest cancer plans (172 fields) of intensity-modulated radiation therapy (IMRT) from Eclipse were selected, of which 30 plans (151 fields) were used for model training and validation, and 4 plans including 21 fields were used for external testing. The collimator misalignment (COLL), monitor unit variation (MU), random multi-leaf collimator shift (MLCR), and systematic MLC shift (MLCS) were introduced. These dose distributions of portal dose predictions for the original plans were defined as the reference dose distribution (RDD), while those for the error-introduced plans were defined as the error-introduced dose distribution (EDD). Different inputs were used in the ResNet for predicting the error magnitude. RESULTS: In the test set, the accuracy of error type prediction based on the dose difference, gamma distribution, and RDD + EDD was 98.36%, 98.91%, and 100%, respectively; the root mean squared error (RMSE) was 1.45-1.54, 0.58-0.90, 0.32-0.36, and 0.15-0.24; the mean absolute error (MAE) was 1.06-1.18, 0.32-0.78, 0.25-0.27, and 0.11-0.18, respectively, for COLL, MU, MLCR and MLCS. CONCLUSIONS: In this study, error magnitude prediction models with dose difference, gamma distribution, and RDD + EDD are established based on ResNet. The accurate prediction of the error magnitude under different error types can provide reference for error analysis in patient-specific QA.

Electroencephalogram findings in 10 patients with post-stroke epilepsy: A retrospective study.

BACKGROUND: Post-stroke epilepsy is a common and easily overlooked complication of acute cerebrovascular disease. Long-term seizures can seriously affect the prognosis and quality of life of patients. Electroencephalogram (EEG) is the simplest way to diagnose epilepsy, and plays an important role in predicting seizures and guiding medication. AIM: To explore the EEG characteristics of patients with post-stroke epilepsy and improve the detection rate of inter-seizure epileptiform discharges. METHODS: From January 2017 to June 2020, 10 patients with post-stroke epilepsy in our hospital were included. The clinical, imaging, and EEG characteristics were collected. The stroke location, seizure type, and ictal and interictal EEG manifestations of the patients with post-stroke epilepsy were then retrospectively analyzed. RESULTS: In all 10 patients, epileptiform waves occurred in the side opposite to the stroke lesion during the interictal stage; these manifested as sharp wave, sharp-wave complex, or spike discharges in the anterior head lead of the side opposite to the lesion. CONCLUSION: In EEG, epileptiform waves can occur in the side opposite to the stroke lesion in patients with post-stroke epilepsy.

Dosimetry and treatment efficiency of SBRT using TaiChiB radiotherapy system for two-lung lesions with one overlapping organs at risk.

Purpose: This study aims to assess the dosimetry and treatment efficiency of TaiChiB-based Stereotactic Body Radiotherapy (SBRT) plans applying to treat two-lung lesions with one overlapping organs at risk. Methods: For four retrospective patients diagnosed with two-lung lesions each patient, four treatment plans were designed including Plan Edge, TaiChiB linac-based, RGS-based, and a linac-RGS hybrid (Plan TCLinac, Plan TCRGS, and Plan TCHybrid). Dosimetric metrics and beam-on time were employed to evaluate and compare the TaiChiB-based plans against Plan Edge. Results: For Conformity Index (CI), Plan TCRGS outperformed all other plans with an average CI of 1.06, as opposed to Plan Edge's 1.33. Similarly, for R50 %, Plan TCRGS was superior with an average R50 % of 3.79, better than Plan Edge's 4.28. In terms of D2 cm, Plan TCRGS also led with an average of 48.48%, compared to Plan Edge's 56.25%. For organ at risk (OAR) sparing, Plan TCRGS often displayed the lowest dosimetric values, notably for the spinal cord (Dmax 5.92 Gy) and lungs (D1500cc 1.00 Gy, D1000cc 2.61 Gy, V10 Gy 15.14%). However, its high Dmax values for the heart and great vessels sometimes exceeded safety thresholds. Plan TCHybrid presented a balanced approach, showing doses comparable to or better than Plan Edge without crossing safety limits. In terms of beam-on time, Plan TCLinac emerged as the most efficient treatment option in three out of four cases, followed closely by Plan Edge in one case. Plan TCRGS, despite its dosimetric advantages, was the least efficient, recording notably longer beam-on times, with a peak at 33.28 minutes in Case 2. Conclusion: For patients with two-lung lesions treated by SBRT whose one lesion overlaps with OARs, the Plan TCHybrid delivered by TaiChiB digital radiotherapy system can be recommended as a clinical option.

Improved viability of probiotics by encapsulation in chickpea protein matrix during simulated gastrointestinal digestion by succinylated modification.

The potential application of succinylated chickpea protein (SCP) as a wall material for spray-dried microencapsulated probiotics was investigated. The results showed that succinylation increased the surface charge of chickpea proteins (CP) and reduced the particle size of the proteins. Meanwhile, succinylated modification decreased the solubility of protein under acidic conditions and increased the solubility in alkaline conditions. The effects of spray drying and in vitro gastrointestinal digestion on probiotics were investigated by microencapsulating chickpea protein with different degrees of N-succinylation. The results showed that all microcapsules had similar morphology, particle size and low water content. The microcapsules prepared by succinylated chickpea protein showed better stability and viability during spray drying and gastrointestinal digestion. The protective effect of probiotics was better as the degree of N-succinylation increased. In particular, the SCP-3-P sample (10 % succinic anhydride modified CP and maltodextrin) lost only 0.29 Log CFU/g throughout gastrointestinal digestion. The superior protective effect provided by succinylated CP in simulated gastric fluid (SGF) was mainly attributed to the reaction of succinic anhydride with protein to cause protein aggregation under gastric acidic conditions, reducing the infiltration of gastric acid and pepsin and maintaining the structural integrity of the microcapsules. Therefore, these findings provide a new strategy for probiotic intestinal delivery and application of chickpea protein.

Efficacy and safety of cold snare polypectomy versus cold endoscopic mucosal resection for resecting 3-10 mm colorectal polyps: Systematic review and meta-analysis of randomized controlled trials.

Introduction The safety and efficacy of cold snare polypectomy (CSP) compared to those of cold endoscopic mucosal resection (CEMR) have been reported. This meta-analysis compared the efficacy and safety of CEMR and CSP. Methods PubMed, EMBASE, Web of Science, and Cochrane Library databases were systematically searched to identify randomized controlled trials comparing the efficacy and safety of CEMR and CSP in removing 3-10 mm polyps. The outcomes assessed included complete resection rate, intraoperative bleeding rate, delayed bleeding rate, perforation, and polyp removal time. The results are reported as risk ratios (RR) and 95% confidence intervals (CI) derived from a Mantel-Haenszel random effects model. Results Seven studies comprising 1,911 polyps were included in the analysis. The complete resection rate of CEMR was comparable to that of CSP (RR: 1.01, 95% CI: 0.99-1.04, P = 0.32). Comparable results were also demonstrated for intraoperative bleeding rate (polyp-based analysis: RR: 1.22, 95% CI: 0.33-4.43, P = 0.77), delayed bleeding rate (polyp-based analysis: RR: 1.34, 95% CI: 0.44-4.15, P = 0.61), and polyp removal time (mean difference: 28.31 s, 95% CI: -21.40~78.02, P=0.26). No studies reported cases of perforation. Conclusion CEMR has comparable efficacy and safety to CSP in removing 3-10 mm polyps. Further randomized controlled trials with long-term follow-up are warranted to compare and validate efficacy.

Investigation of PET image quality with acquisition time/bed and enhancement of lesion quantification accuracy through deep progressive learning.

OBJECTIVE: To improve the PET image quality by a deep progressive learning (DPL) reconstruction algorithm and evaluate the DPL performance in lesion quantification. METHODS: We reconstructed PET images from 48 oncological patients using ordered subset expectation maximization (OSEM) and deep progressive learning (DPL) methods. The patients were enrolled into three overlapped studies: 11 patients for image quality assessment (study 1), 34 patients for sub-centimeter lesion quantification (study 2), and 28 patients for imaging of overweight or obese individuals (study 3). In study 1, we evaluated the image quality visually based on four criteria: overall score, image sharpness, image noise, and diagnostic confidence. We also measured the image quality quantitatively using the signal-to-background ratio (SBR), signal-to-noise ratio (SNR), contrast-to-background ratio (CBR), and contrast-to-noise ratio (CNR). To evaluate the performance of the DPL algorithm in quantifying lesions, we compared the maximum standardized uptake values (SUVmax), SBR, CBR, SNR and CNR of 63 sub-centimeter lesions in study 2 and 44 lesions in study 3. RESULTS: DPL produced better PET image quality than OSEM did based on the visual evaluation methods when the acquisition time was 0.5, 1.0 and 1.5 min/bed. However, no discernible differences were found between the two methods when the acquisition time was 2.0, 2.5 and 3.0 min/bed. Quantitative results showed that DPL had significantly higher values of SBR, CBR, SNR, and CNR than OSEM did for each acquisition time. For sub-centimeter lesion quantification, the SUVmax, SBR, CBR, SNR, and CNR of DPL were significantly enhanced, compared with OSEM. Similarly, for lesion quantification in overweight and obese patients, DPL significantly increased these parameters compared with OSEM. CONCLUSION: The DPL algorithm dramatically enhanced the quality of PET images and enabled more accurate quantification of sub-centimeters lesions in patients and lesions in overweight or obese patients. This is particularly beneficial for overweight or obese patients who usually have lower image quality due to the increased attenuation.

Modified Bushen Yiqi Formula mitigates pulmonary inflammation and airway remodeling by inhibiting neutrophils chemotaxis and IL17 signaling pathway in rats with COPD.

ETHNOPHARMACOLOGICAL RELEVANCE: Chronic obstructive pulmonary disease (COPD) is a major global health concern characterized by pulmonary inflammation and airway remodeling. Traditional Chinese medicine, such as Modified Jiawei Bushen Yiqi Formula (MBYF), has been used as a complementary therapy for COPD in China. AIM OF THE STUDY: To investigate the therapeutic potential of MBYF in a rat model of COPD induced by cigarette smoke (CS) exposure and explore the underlying mechanism. MATERIALS AND METHODS: The COPD rat model was established through 24 weeks of CS exposure, with MBYF administration starting in the 9th week. Pulmonary function, histological analysis, inflammatory cell count and molecular assays were employed to assess the effects of MBYF on airway remodeling, pulmonary inflammation, neutrophils chemotaxis and the IL17 signaling pathway. RESULTS: MBYF treatment effectively delayed airway remodeling, as evidenced by improved pulmonary function parameters. Histological examination and bronchoalveolar lavage fluid analysis revealed that MBYF mitigated CS-induced pulmonary inflammation by reducing inflammatory cell infiltration. Pharmacological network analysis suggested that MBYF may act through the IL17 signaling pathway to regulate inflammatory responses. RNA-sequencing and molecular assays indicated that MBYF inhibited neutrophils chemotaxis through downregulating the CXCL1/CXCL5/CXCL8-CXCR2 axis, and suppressed IL17A, IL17F and its downstream cytokines, including IL6, TNFα, IL1ß, and COX2. Furthermore, MBYF inhibited the activation of NF-κB and MAPKs in the IL17 signaling pathway. CONCLUSION: MBYF exhibits potential as an adjunct or alternative treatment for COPD, effectively mitigating CS-induced pulmonary inflammation and airway remodeling through the inhibition of neutrophil chemotaxis and IL17 signaling pathway.

Scrutiny of genome-wide somatic mutation profiles in centenarians identifies the key genomic regions for human longevity.

Somatic mutations accumulate with age and are associated closely with human health, their characterization in longevity cohorts remains largely unknown. Here, by analyzing whole genome somatic mutation profiles in 73 centenarians and 51 younger controls in China, we found that centenarian genomes are characterized by a markedly skewed distribution of somatic mutations, with many genomic regions being specifically conserved but displaying a high function potential. This, together with the observed more efficient DNA repair ability in the long-lived individuals, supports the existence of key genomic regions for human survival during aging, with their integrity being of essential to human longevity.

Chemical constituents from the aerial parts of Rubia cordifolia L. with their NO inhibitory activity.

A new naphthoquinone derivative (1) together with twenty-three known compounds (2-24), were isolated from the aerial parts of Rubia cordifolia L. Their structures were elucidated on the basis of NMR and HR-ESIMS data. Compounds 1-13 were assessed for their inhibitory effects on NO production in LPS-stimulated RAW 264.7 macrophage cells. Compounds 2-6 exhibited significant inhibitory activities with IC50 values of 21.37, 13.81, 24.56, 20.32, and 30.08 µmol·L-1, respectively.

AS-NeSt: A Novel 3D Deep Learning Model for Radiation Therapy Dose Distribution Prediction in Esophageal Cancer Treatment With Multiple Prescriptions.

PURPOSE: Implementing artificial intelligence technologies allows for the accurate prediction of radiation therapy dose distributions, enhancing treatment planning efficiency. However, esophageal cancers present unique challenges because of tumor complexity and diverse prescription types. Additionally, limited data availability hampers the effectiveness of existing artificial intelligence models. This study developed a deep learning model, trained on a diverse data set of esophageal cancer prescriptions, to improve dose prediction accuracy. METHODS AND MATERIALS: We retrospectively collected data from 530 patients with esophageal cancer, including single-target and simultaneous integrated boost prescriptions, for model building. The proposed Asymmetric ResNeSt (AS-NeSt) model features novel 3-dimensional (3D) ResNeSt blocks and an asymmetrical architecture. We constructed a loss function targeting global and local doses and validated the model's performance against existing alternatives. Model-assisted experiments were used to validate its clinical benefits. RESULTS: The AS-NeSt model maintained an absolute prediction error below 5% for each dosimetric metric. The average Dice similarity coefficient for isodose volumes was 0.93. The model achieved an average relative prediction error of 2.02%, statistically lower than Hierarchically Densely Connected U-net (4.17%), DoseNet (2.35%), and Densely Connected Network (3.65%). It also demonstrated significantly fewer parameters and shorter prediction times. Clinically, the AS-NeSt model raised physicians' ability to accurately preassess appropriate treatment methods before planning from 95.24% to 100%, reduced planning time by over 61% for junior dosimetrists and 52% for senior dosimetrists, and decreased both inter- and intra-dosimetrist discrepancies by more than 50%. CONCLUSIONS: The AS-NeSt model, developed with innovative 3D ResNeSt blocks and an asymmetrical encoder-decoder structure, has been validated using clinical esophageal cancer patient data. It accurately predicts 3D dose distributions for various prescriptions, including simultaneous integrated boost, showing potential to improve the management of esophageal cancer treatment in a clinical setting.

Advances in Neuroimaging and Multiple Post-Processing Techniques for Epileptogenic Zone Detection of Drug-Resistant Epilepsy.

Among the approximately 20 million patients with drug-resistant epilepsy (DRE) worldwide, the vast majority can benefit from surgery to minimize seizure reduction and neurological impairment. Precise preoperative localization of epileptogenic zone (EZ) and complete resection of the lesions can influence the postoperative prognosis. However, precise localization of EZ is difficult, and the structural and functional alterations in the brain caused by DRE vary by etiology. Neuroimaging has emerged as an approach to identify the seizure-inducing structural and functional changes in the brain, and magnetic resonance imaging (MRI) and positron emission tomography (PET) have become routine noninvasive imaging tools for preoperative evaluation of DRE in many epilepsy treatment centers. Multimodal neuroimaging offers unique advantages in detecting EZ, especially in improving the detection rate of patients with negative MRI or PET findings. This approach can characterize the brain imaging characteristics of patients with DRE caused by different etiologies, serving as a bridge between clinical and pathological findings and providing a basis for individualized clinical treatment plans. In addition to the integration of multimodal imaging modalities and the development of special scanning sequences and image post-processing techniques for early and precise localization of EZ, the application of deep machine learning for extracting image features and deep learning-based artificial intelligence have gradually improved diagnostic efficiency and accuracy. These improvements can provide clinical assistance for precisely outlining the scope of EZ and indicating the relationship between EZ and functional brain areas, thereby enabling standardized and precise surgery and ensuring good prognosis. However, most existing studies have limitations imposed by factors such as their small sample sizes or hypothesis-based study designs. Therefore, we believe that the application of neuroimaging and post-processing techniques in DRE requires further development and that more efficient and accurate imaging techniques are urgently needed in clinical practice. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 2.

Combination therapy of methotrexate and iguratimod for female patients with moderate to severe active rheumatoid arthritis and its impact on ovarian function.

Rheumatoid arthritis is systemic inflammatory disease, presenting as symmetrical polyarthritis, mainly affecting hands and feet. Female patients with rheumatoid arthritis have also decreased fertility and premature ovarian failure. Methotrexate is used in treatment of rheumatoid arthritis. However, single treatment of Methotrexate is not ideal and often needs to be combined with other drugs like Iguratimod for intensive treatment of refractory rheumatoid arthritis. We aim to explore efficacy of combined use of MTX and IGU for female patients with rheumatoid arthritis and its impact on ovarian reserve function. Total 80 female patients with moderate to severe active rheumatoid arthritis were selected and randomly divided into MTX and MTX + IGU groups. The MTX + IGU group showed lower levels of IL-1ß, IL-6, IL-17 and TNF-α after treatment as compared to MTX group. The MTX + IGU group showed significantly higher level of AMH at the end of treatment. However, no statistical differences were observed in FSH, LH, E2 and AFC levels between the two groups. The combined therapy of MTX and IGU has better efficacy with less impact on ovarian function, even improving ovarian reserve function through effective control of rheumatoid inflammatory activity.

DelicacyNet for nutritional evaluation of recipes.

In this paper, we are interested in how computers can be used to better serve us humans, such as helping humans control their nutrient intake, with higher level shortcuts. Specifically, the neural network model was used to help humans identify and analyze the content and proportion of nutrients in daily food intake, so as to help humans autonomously choose and reasonably match diets. In this study, we formed the program we wanted to obtain by establishing four modules, in which the imagination module sampled the environment, then relied on the encoder to extract the implicit features of the image, and finally relied on the decoder to obtain the required feature vector from the implicit features, and converted it into the battalion formation table information through the semantic output module. Finally, the model achieved extremely high accuracy on recipe1M+ and food2K datasets.

Compound heterozygous mutations in tripeptidyl peptidase 1 cause rare autosomal recessive spinocerebellar ataxia type 7: A case report.

BACKGROUND: Spinocerebellar ataxia recessive type 7 (SCAR7) is a rare clinical manifestation beginning in childhood or adolescence. SCAR7 is caused by tripeptidyl peptidase 1 (TPP1) gene mutations, and presents with cerebellar ataxia, pyramidal signs, neurocognitive impairment, deep paresthesia, and cerebellar atrophy. CASE SUMMARY: Here, we describe a 25-year-old female patient in China who presented with increasing difficulty walking, falling easily, shaking limbs, instability holding items, slurred speech, coughing when drinking, palpitations, and frequent hunger and overeating. Magnetic resonance imaging showed cerebellar atrophy. Whole exome sequencing detected two compound heterozygous mutations in the TPP1 gene: c.1468G>A p.Glu490Lys and c.1417G>A p.Gly473Arg. Considering the patient's clinical presentation and genetic test results, we hypothesized that complex heterozygous mutations cause TPP1 enzyme deficiency, which may lead to SCAR7. CONCLUSION: We report the first case of SCAR7 from China. We also identify novel compound heterozygous mutations in the TPP1 gene associated with SCAR7, expanding the range of known disease-causing mutations for SCAR7.