Lrp10 suppresses IL7R limiting CD8 T cell homeostatic expansion and anti-tumor immunity.

Signals emanating from the T-cell receptor (TCR), co-stimulatory receptors, and cytokine receptors each influence CD8 T-cell fate. Understanding how these signals respond to homeostatic and microenvironmental cues can reveal new ways to therapeutically direct T-cell function. Through forward genetic screening in mice, we discover that loss-of-function mutations in LDL receptor-related protein 10 (Lrp10) cause naive and central memory CD8 T cells to accumulate in peripheral lymphoid organs. Lrp10 encodes a conserved cell surface protein of unknown immunological function. T-cell activation induces Lrp10 expression, which post-translationally suppresses IL7 receptor (IL7R) levels. Accordingly, Lrp10 deletion enhances T-cell homeostatic expansion through IL7R signaling. Lrp10-deficient mice are also intrinsically resistant to syngeneic tumors. This phenotype depends on dense tumor infiltration of CD8 T cells, which display increased memory cell characteristics, reduced terminal exhaustion, and augmented responses to immune checkpoint inhibition. Here, we present Lrp10 as a new negative regulator of CD8 T-cell homeostasis and a host factor that controls tumor resistance with implications for immunotherapy.

Fast Model Selection and Hyperparameter Tuning for Generative Models.

Generative models have gained significant attention in recent years. They are increasingly used to estimate the underlying structure of high-dimensional data and artificially generate various kinds of data similar to those from the real world. The performance of generative models depends critically on a good set of hyperparameters. Yet, finding the right hyperparameter configuration can be an extremely time-consuming task. In this paper, we focus on speeding up the hyperparameter search through adaptive resource allocation, early stopping underperforming candidates quickly and allocating more computational resources to promising ones by comparing their intermediate performance. The hyperparameter search is formulated as a non-stochastic best-arm identification problem where resources like iterations or training time constrained by some predetermined budget are allocated to different hyperparameter configurations. A procedure which uses hypothesis testing coupled with Successive Halving is proposed to make the resource allocation and early stopping decisions and compares the intermediate performance of generative models by their exponentially weighted Maximum Means Discrepancy (MMD). The experimental results show that the proposed method selects hyperparameter configurations that lead to a significant improvement in the model performance compared to Successive Halving for a wide range of budgets across several real-world applications.

One-Year Outcome After Endovascular Treatment for Acute Basilar Artery Occlusion.

BACKGROUND AND PURPOSE: The BASILAR registry, a nationwide prospective nonrandomized study conducted in China, enrolled consecutive patients with acute basilar artery occlusion receiving endovascular treatment or conventional-treatment from January 2014 to May 2019. This article aimed to report the results of clinical follow-up at one year among these patients. METHODS: The primary outcome was the modified Rankin Scale at one year, assessed as a common odds ratio using ordinal logistic regression analysis adjusted for prespecified prognostic factors. Secondary outcomes included the modified Rankin Scale-based outcome group at one year (0-1, 0-2, or 0-3) and all-cause death. RESULTS: Of the 829 patients enrolled in the original BASILAR registry, one-year data were available for 785 patients (94.7%). The distribution of outcomes on the modified Rankin Scale favored endovascular treatment over conventional-treatment (adjusted common odds ratio, 4.50 [95% CI, 2.81-7.29]; P<0.001). The cumulative one-year mortality rate was 54.6% in the endovascular treatment group versus 83.5% in the conventional-treatment group (adjusted odds ratio, 4.36 [95% CI, 2.69-7.29]; P<0.001). CONCLUSIONS: The beneficial effect of endovascular treatment on functional outcome at one year in patients with acute basilar artery occlusion is similar to that reported at 90 days in the original study. REGISTRATION: URL: http://www.chictr.org.cn; Unique identifier: ChiCTR1800014759.

Deep Phenotyping of Chinese Electronic Health Records by Recognizing Linguistic Patterns of Phenotypic Narratives With a Sequence Motif Discovery Tool: Algorithm Development and Validation.

BACKGROUND: Phenotype information in electronic health records (EHRs) is mainly recorded in unstructured free text, which cannot be directly used for clinical research. EHR-based deep-phenotyping methods can structure phenotype information in EHRs with high fidelity, making it the focus of medical informatics. However, developing a deep-phenotyping method for non-English EHRs (ie, Chinese EHRs) is challenging. Although numerous EHR resources exist in China, fine-grained annotation data that are suitable for developing deep-phenotyping methods are limited. It is challenging to develop a deep-phenotyping method for Chinese EHRs in such a low-resource scenario. OBJECTIVE: In this study, we aimed to develop a deep-phenotyping method with good generalization ability for Chinese EHRs based on limited fine-grained annotation data. METHODS: The core of the methodology was to identify linguistic patterns of phenotype descriptions in Chinese EHRs with a sequence motif discovery tool and perform deep phenotyping of Chinese EHRs by recognizing linguistic patterns in free text. Specifically, 1000 Chinese EHRs were manually annotated based on a fine-grained information model, PhenoSSU (Semantic Structured Unit of Phenotypes). The annotation data set was randomly divided into a training set (n=700, 70%) and a testing set (n=300, 30%). The process for mining linguistic patterns was divided into three steps. First, free text in the training set was encoded as single-letter sequences (P: phenotype, A: attribute). Second, a biological sequence analysis tool-MEME (Multiple Expectation Maximums for Motif Elicitation)-was used to identify motifs in the single-letter sequences. Finally, the identified motifs were reduced to a series of regular expressions representing linguistic patterns of PhenoSSU instances in Chinese EHRs. Based on the discovered linguistic patterns, we developed a deep-phenotyping method for Chinese EHRs, including a deep learning-based method for named entity recognition and a pattern recognition-based method for attribute prediction. RESULTS: In total, 51 sequence motifs with statistical significance were mined from 700 Chinese EHRs in the training set and were combined into six regular expressions. It was found that these six regular expressions could be learned from a mean of 134 (SD 9.7) annotated EHRs in the training set. The deep-phenotyping algorithm for Chinese EHRs could recognize PhenoSSU instances with an overall accuracy of 0.844 on the test set. For the subtask of entity recognition, the algorithm achieved an F1 score of 0.898 with the Bidirectional Encoder Representations from Transformers-bidirectional long short-term memory and conditional random field model; for the subtask of attribute prediction, the algorithm achieved a weighted accuracy of 0.940 with the linguistic pattern-based method. CONCLUSIONS: We developed a simple but effective strategy to perform deep phenotyping of Chinese EHRs with limited fine-grained annotation data. Our work will promote the second use of Chinese EHRs and give inspiration to other non-English-speaking countries.

Thermal face recognition under different conditions.

BACKGROUND: A thermal face recognition under different conditions is proposed in this article. The novelty of the proposed method is applying temperature information in the recognition of thermal face. The physiological information is obtained from the face using a thermal camera, and a machine learning classifier is utilized for thermal face recognition. The steps of preprocessing, feature extraction and classification are incorporated in training phase. First of all, by using Bayesian framework, the human face can be extracted from thermal face image. Several thermal points are selected as a feature vector. These points are utilized to train Random Forest (RF). Random Forest is a supervised learning algorithm. It is an ensemble of decision trees. Namely, RF merges multiple decision trees together to obtain a more accurate classification. Feature vectors from the testing image are fed into the classifier for face recognition. RESULTS: Experiments were conducted under different conditions, including normal, adding noise, wearing glasses, face mask, and glasses with mask. To compare the performance with the convolutional neural network-based technique, experimental results of the proposed method demonstrate its robustness against different challenges. CONCLUSIONS: Comparisons with other techniques demonstrate that the proposed method is robust under less feature points, which is around one twenty-eighth to one sixtieth of those by other classic methods.

Values of Baseline Posterior Circulation Acute Stroke Prognosis Early Computed Tomography Score for Treatment Decision of Acute Basilar Artery Occlusion.

BACKGROUND AND PURPOSE: This study aimed to analyze the impact of baseline posterior circulation Acute Stroke Prognosis Early Computed Tomography Score (pc-ASPECTS) on the efficacy and safety of endovascular therapy (EVT) for patients with acute basilar artery occlusion. METHODS: The BASILAR was a nationwide prospective registry of consecutive patients with a symptomatic and radiologically confirmed acute basilar artery occlusion within 24 hours of symptom onset. We estimated the effect of standard medical therapy alone (SMT group) versus SMT plus EVT (EVT group) for patients with documented pc-ASPECTS on noncontrast CT, both as a categorical (0-4 versus 5-7 versus 8-10) and as a continuous variable. The primary outcomes included favorable functional outcomes (modified Rankin Scale ≤3) at 90 days and mortality within 90 days. RESULTS: In total, 823 cases were included: 468 with pc-ASPECTS 8 to 10 (SMT: 71; EVT: 397), 317 with pc-ASPECTS 5 to 7 (SMT: 85; EVT: 232), and 38 with pc-ASPECTS 0 to 4 (SMT: 13; EVT: 25). EVT was associated with higher rate of favorable outcomes (adjusted relative risk with 95% CI, 4.35 [1.30-14.48] and 3.20 [1.68-6.09]; respectively) and lower mortality (60.8% versus 77.6%, P=0.005 and 35.0% versus 66.2%, P<0.001; respectively) than SMT in the pc-ASPECTS 5 to 7 and 8 to 10 subgroups. Continuous benefit curves also showed the superior efficacy and safety of EVT over SMT in patients with pc-ASPECTS ≥5. Furthermore, the prognostic effect of onset to puncture time on favorable outcome with EVT was not significant after adjustment for pc-ASPECTS (adjusted odds ratio, 0.98 [95% CI, 0.94-1.02]). CONCLUSIONS: Patients of basilar artery occlusion with pc-ASPECTS ≥5 could benefit from EVT. The baseline pc-ASPECTS appears more important for decision making and predicting prognosis than time to EVT. Registration: URL: http://www.chictr.org.cn. Unique identifier: ChiCTR1800014759.

Correction: Constructing High-Fidelity Phenotype Knowledge Graphs for Infectious Diseases With a Fine-Grained Semantic Information Model: Development and Usability Study.

[This corrects the article DOI: 10.2196/26892.].

Constructing High-Fidelity Phenotype Knowledge Graphs for Infectious Diseases With a Fine-Grained Semantic Information Model: Development and Usability Study.

BACKGROUND: Phenotypes characterize the clinical manifestations of diseases and provide important information for diagnosis. Therefore, the construction of phenotype knowledge graphs for diseases is valuable to the development of artificial intelligence in medicine. However, phenotype knowledge graphs in current knowledge bases such as WikiData and DBpedia are coarse-grained knowledge graphs because they only consider the core concepts of phenotypes while neglecting the details (attributes) associated with these phenotypes. OBJECTIVE: To characterize the details of disease phenotypes for clinical guidelines, we proposed a fine-grained semantic information model named PhenoSSU (semantic structured unit of phenotypes). METHODS: PhenoSSU is an "entity-attribute-value" model by its very nature, and it aims to capture the full semantic information underlying phenotype descriptions with a series of attributes and values. A total of 193 clinical guidelines for infectious diseases from Wikipedia were selected as the study corpus, and 12 attributes from SNOMED-CT were introduced into the PhenoSSU model based on the co-occurrences of phenotype concepts and attribute values. The expressive power of the PhenoSSU model was evaluated by analyzing whether PhenoSSU instances could capture the full semantics underlying the descriptions of the corresponding phenotypes. To automatically construct fine-grained phenotype knowledge graphs, a hybrid strategy that first recognized phenotype concepts with the MetaMap tool and then predicted the attribute values of phenotypes with machine learning classifiers was developed. RESULTS: Fine-grained phenotype knowledge graphs of 193 infectious diseases were manually constructed with the BRAT annotation tool. A total of 4020 PhenoSSU instances were annotated in these knowledge graphs, and 3757 of them (89.5%) were found to be able to capture the full semantics underlying the descriptions of the corresponding phenotypes listed in clinical guidelines. By comparison, other information models, such as the clinical element model and the HL7 fast health care interoperability resource model, could only capture the full semantics underlying 48.4% (2034/4020) and 21.8% (914/4020) of the descriptions of phenotypes listed in clinical guidelines, respectively. The hybrid strategy achieved an F1-score of 0.732 for the subtask of phenotype concept recognition and an average weighted accuracy of 0.776 for the subtask of attribute value prediction. CONCLUSIONS: PhenoSSU is an effective information model for the precise representation of phenotype knowledge for clinical guidelines, and machine learning can be used to improve the efficiency of constructing PhenoSSU-based knowledge graphs. Our work will potentially shift the focus of medical knowledge engineering from a coarse-grained level to a more fine-grained level.

Effect of Endovascular Treatment Alone vs Intravenous Alteplase Plus Endovascular Treatment on Functional Independence in Patients With Acute Ischemic Stroke: The DEVT Randomized Clinical Trial.

Importance: For patients with large vessel occlusion strokes, it is unknown whether endovascular treatment alone compared with intravenous thrombolysis plus endovascular treatment (standard treatment) can achieve similar functional outcomes. Objective: To investigate whether endovascular thrombectomy alone is noninferior to intravenous alteplase followed by endovascular thrombectomy for achieving functional independence at 90 days among patients with large vessel occlusion stroke. Design, Setting, and Participants: Multicenter, randomized, noninferiority trial conducted at 33 stroke centers in China. Patients (n = 234) were 18 years or older with proximal anterior circulation intracranial occlusion strokes within 4.5 hours from symptoms onset and eligible for intravenous thrombolysis. Enrollment took place from May 20, 2018, to May 2, 2020. Patients were enrolled and followed up for 90 days (final follow-up was July 22, 2020). Interventions: A total of 116 patients were randomized to the endovascular thrombectomy alone group and 118 patients to combined intravenous thrombolysis and endovascular thrombectomy group. Main Outcomes and Measures: The primary end point was the proportion of patients achieving functional independence at 90 days (defined as score 0-2 on the modified Rankin Scale; range, 0 [no symptoms] to 6 [death]). The noninferiority margin was -10%. Safety outcomes included the incidence of symptomatic intracerebral hemorrhage within 48 hours and 90-day mortality. Results: The trial was stopped early because of efficacy when 234 of a planned 970 patients had undergone randomization. All 234 patients who were randomized (mean age, 68 years; 102 women [43.6%]) completed the trial. At the 90-day follow-up, 63 patients (54.3%) in the endovascular thrombectomy alone group vs 55 (46.6%) in the combined treatment group achieved functional independence at the 90-day follow-up (difference, 7.7%, 1-sided 97.5% CI, -5.1% to ∞)P for noninferiority = .003). No significant between-group differences were detected in symptomatic intracerebral hemorrhage (6.1% vs 6.8%; difference, -0.8%; 95% CI, -7.1% to 5.6%) and 90-day mortality (17.2% vs 17.8%; difference, -0.5%; 95% CI, -10.3% to 9.2%). Conclusions and Relevance: Among patients with ischemic stroke due to proximal anterior circulation occlusion within 4.5 hours from onset, endovascular treatment alone, compared with intravenous alteplase plus endovascular treatment, met the prespecified statistical threshold for noninferiority for the outcome of 90-day functional independence. These findings should be interpreted in the context of the clinical acceptability of the selected noninferiority threshold. Trial Registration: Chinese Clinical Trial Registry: ChiCTR-IOR-17013568.

LATTE: A knowledge-based method to normalize various expressions of laboratory test results in free text of Chinese electronic health records.

BACKGROUND: A wealth of clinical information is buried in free text of electronic health records (EHR), and converting clinical information to machine-understandable form is crucial for the secondary use of EHRs. Laboratory test results, as one of the most important types of clinical information, are written in various styles in free text of EHRs. This has brought great difficulties for data integration and utilization of EHRs. Therefore, developing technology to normalize different expressions of laboratory test results in free text is indispensable for the secondary use of EHRs. METHODS: In this study, we developed a knowledge-based method named LATTE (transforming lab test results), which could transform various expressions of laboratory test results into a normalized and machine-understandable format. We first identified the analyte of a laboratory test result with a dictionary-based method and then designed a series of rules to detect information associated with the analyte, including its specimen, measured value, unit of measure, conclusive phrase and sampling factor. We determined whether a test result is normal or abnormal by understanding the meaning of conclusive phrases or by comparing its measured value with an appropriate normal range. Finally, we converted various expressions of laboratory test results, either in numeric or textual form, into a normalized form as "specimen-analyte-abnormality". With this method, a laboratory test with the same type of abnormality would have the same representation, regardless of the way that it is mentioned in free text. RESULTS: LATTE was developed and optimized on a training set including 8894 laboratory test results from 756 EHRs, and evaluated on a test set including 3740 laboratory test results from 210 EHRs. Compared to experts' annotations, LATTE achieved a precision of 0.936, a recall of 0.897 and an F1 score of 0.916 on the training set, and a precision of 0.892, a recall of 0.843 and an F1 score of 0.867 on the test set. For 223 laboratory tests with at least two different expression forms in the test set, LATTE transformed 85.7% (2870/3350) of laboratory test results into a normalized form. Besides, LATTE achieved F1 scores above 0.8 for EHRs from 18 of 21 different hospital departments, indicating its generalization capabilities in normalizing laboratory test results. CONCLUSION: In conclusion, LATTE is an effective method for normalizing various expressions of laboratory test results in free text of EHRs. LATTE will facilitate EHR-based applications such as cohort querying, patient clustering and machine learning. AVAILABILITY: LATTE is freely available for download on GitHub (https://github.com/denglizong/LATTE).

Enhancement of scutellarin oral delivery efficacy by vitamin B12-modified amphiphilic chitosan derivatives to treat type II diabetes induced-retinopathy.

BACKGROUND: Diabetic retinopathy is the most common complication in diabetic patients relates to high expression of VEGF and microaneurysms. Scutellarin (Scu) turned out to be effective against diabetes related vascular endothelial cell dysfunction. However, its clinical applications have been limited by its low bioavailability. In this study, we formulated and characterized a novel intestinal target nanoparticle carrier based on amphiphilic chitosan derivatives (Chit-DC-VB12) loaded with scutellarin to enhance its bioavailability and then evaluated its therapeutic effect in experimental diabetic retinopathy model. RESULTS: Chit-DC-VB12 nanoparticles showed low toxicity toward the human colon adenocarcinoma (Caco-2) cells and zebra fish within concentration of 250 µg/ml, owing to good biocompatibility of chitosan. The scutellarin-loaded Chit-DC-VB12 nanoparticles (Chit-DC-VB12-Scu) were then prepared by self-assembly in aqueous solution. Scanning electron microscopy and dynamic light scattering analysis indicated that the Chit-DC-VB12-Scu nanoparticles were spherical particles in the sizes ranging from 150 to 250 nm. The Chit-DC-VB12-Scu nanoparticles exhibited high permeation in Caco-2 cell, indicated it could be beneficial to be absorbed in humans. We also found that Chit-DC-VB12 nanoparticles had a high cellular uptake. Bioavailability studies were performed in Sprague-Dawley rats, which present the area under the curve of scutellarin of Chit-DC-VB12-Scu was two to threefolds greater than that of free scutellarin alone. Further to assess the therapeutic efficacy of diabetic retinopathy, we showed Chit-DC-VB12-Scu down-regulated central retinal artery resistivity index and the expression of angiogenesis proteins (VEGF, VEGFR2, and vWF) of retinas in type II diabetic rats. CONCLUSIONS: Chit-DC-VB12 nanoparticles loaded with scutellarin have better bioavailability and cellular uptake efficiency than Scu, while Chit-DC-VB12-Scu nanoparticles alleviated the structural disorder of intraretinal neovessels in the retina induced by diabetes, and it also inhibited the retinal neovascularization via down-regulated the expression of angiogenesis proteins. In conclusion, the Chit-DC-VB12 nanoparticles enhanced scutellarin oral delivery efficacy and exhibited potential as small intestinal target promising nano-carriers for treatment of type II diabetes induced-retinopathy.

Mitochondrial EF4 links respiratory dysfunction and cytoplasmic translation in Caenorhabditis elegans.

How animals coordinate cellular bioenergetics in response to stress conditions is an essential question related to aging, obesity and cancer. Elongation factor 4 (EF4/LEPA) is a highly conserved protein that promotes protein synthesis under stress conditions, whereas its function in metazoans remains unknown. Here, we show that, in Caenorhabditis elegans, the mitochondria-localized CeEF4 (referred to as mtEF4) affects mitochondrial functions, especially at low temperature (15°C). At worms' optimum growing temperature (20°C), mtef4 deletion leads to self-brood size reduction, growth delay and mitochondrial dysfunction. Transcriptomic analyses show that mtef4 deletion induces retrograde pathways, including mitochondrial biogenesis and cytoplasmic translation reorganization. At low temperature (15°C), mtef4 deletion reduces mitochondrial translation and disrupts the assembly of respiratory chain supercomplexes containing complex IV. These observations are indicative of the important roles of mtEF4 in mitochondrial functions and adaptation to stressful conditions.

The Hb H disease genotypes in Southern China.

Abstract We report the genetic data of 435 patients with Hb H (ß4) disease who presented at our center between 2005 and 2012. Our results showed that all patients had the Southeast Asian deletion (- -(SEA)) on one allele. The -α(3.7) (rightward) deletion was the most common on the other allele, followed by the -α(4.2) (leftward) deletion, Hb Constant Spring (Hb CS, α142, Term → Gln; HBA2: c.427T > C) and Hb Quong Sze [Hb QS, α125(H8)Leu → Pro; HBA2: c.377T > C] mutations. Two rare point mutations, α31(B12)Arg → Lys; HBA2: c.95G > A and Hb Zurich Albisrieden [α59(E8)Gly → Arg; HBA1: c.178G > C], were also identified. Four patients had a concomitant ß-thalassemia (ß-thal) heterozygosity. Our results reflect the genetic heterogeneity of Hb H disease and the interaction between Hb H disease and ß-thal trait in Southern China.

[Analysis of OCRL gene mutation in a male infant with Lowe syndrome].

OBJECTIVE: To identify pathological mutation in a Chinese male infant featuring oculocerebrorenal syndrome (also called Lowe syndrome). METHODS: Clinical data of the patient were collected. DNA was extracted from peripheral blood of the infant and his parents. All of the 24 exons and intron-exon splice sites of OCRL gene were amplified with PCR. Mutations were detected by direct sequencing the PCR products. RESULTS: The infant was found to have carried a c.1499G>A (p.R500Q) mutation in exon 15 of the OCRL gene, which was transmitted from his mother, who was heterozygous for the same mutation. The c.1499G>A mutation, discovered in Chinese population for the first time, has been reported to cause severe Lowe syndrome in other ethnic populations. CONCLUSION: The c.1499G>A mutation of the OCRL gene is probably responsible for the disease in the patient. Further study of this mutation may facilitate delineation of the genotype-phenotype correlation of this disease.

Atomic-scale Ru anchored on chromium-shavings as a precursor for a pH-universal hydrogen evolution reaction electrocatalyst.

In the leather manufacturing industry, the management of substantial quantities of solid waste containing chrome shavings remains a formidable challenge. Concurrently, there is a pressing need for the development of pH-universal and economically viable electrocatalysts for the hydrogen evolution reaction (HER). In response to these intertwined challenges, this study proposes an innovative approach wherein the amino groups present on the surface of chrome shavings are utilized to immobilize single ruthenium atoms during pyrolysis, thereby facilitating the synthesis of hydrogen evolution electrocatalysts. The optimized sample, denoted as CN/Cr2O3/Ru-1, demonstrates exceptional electrocatalytic performance, exhibiting an ultra-low overpotential of -28 mV in 1.0 M KOH at a current density of 10 mA cm-2, and it also exhibits good performance in acidic and neutral electrolytes. Importantly, these overpotentials surpass those reported for many previous ruthenium-based catalysts. Density functional theory (DFT) calculations elucidate that both oxygen (O) and chromium (Cr) moieties within Cr2O3 can engage in favorable interactions with the coordination patterns of the ruthenium (Ru) atoms, thereby elucidating the synergistic enhancement conferred by the chromium element in CN/Cr2O3/Ru, which ultimately facilitates and promotes the catalytic activity of the ruthenium atoms serving as the catalytic center. This facile synthesis route not only presents a green solution for addressing waste chromium pollutants but also offers a promising avenue for the development of high-performance, cost-efficient electrocatalysts.

[Mutation analysis for a Chinese family featuring X-linked alpha thalassemia/mental retardation syndrome].

OBJECTIVE: To identify potential mutation in a Chinese family featuring X-linked alpha thalassemia/mental retardation syndrome (ATR-X). METHODS: Based on clinical symptoms and inheritance pattern, linkage analysis of X chromosome short tandem repeats (X-STR) loci was carried out to locate the candidate gene. Subsequently, sequences of exons and exon-intron boundaries of the candidate gene were amplified with polymerase chain reaction (PCR). Potential mutations were detected by direct DNA sequencing. All patients were also analyzed for the trait of thalassemia. RESULTS: Linkage analysis indicated the candidate gene to be ATRX. Subsequently, a homozygous missense mutation c.736C>T (p.R246C) was found in exon 9 of ATRX in all of the 3 patients. And a heterozygous mutation c.736C>T (p.R246C) was also identified in the patient's mother and grandmother. Similar mutations were not detected in other members of the family. Alpha thalassemia was detected in the proband and another patient, whose genotypes were determined as -α(3.7)/αα and --(sea)/αα, respectively. CONCLUSION: Missense mutation of c.736C>T in ATRX gene is a mutation hotspot, and p.R246C may disturb the function of ATRX-DNMT3-DNMT3L domain (ADD), which may be responsible for the disease in this family.

TeaBERT: An Efficient Knowledge Infused Cross-Lingual Language Model for Mapping Chinese Medical Entities to the Unified Medical Language System.

Medical entity normalization is an important task for medical information processing. The Unified Medical Language System (UMLS), a well-developed medical terminology system, is crucial for medical entity normalization. However, the UMLS primarily consists of English medical terms. For languages other than English, such as Chinese, a significant challenge for normalizing medical entities is the lack of robust terminology systems. To address this issue, we propose a translation-enhancing training strategy that incorporates the translation and synonym knowledge of the UMLS into a language model using the contrastive learning approach. In this work, we proposed a cross-lingual pre-trained language model called TeaBERT, which can align synonymous Chinese and English medical entities across languages at the concept level. As the evaluation results showed, the TeaBERT language model outperformed previous cross-lingual language models with Acc@5 values of 92.54%, 87.14% and 84.77% on the ICD10-CN, CHPO and RealWorld-v2 datasets, respectively. It also achieved a new state-of-the-art cross-lingual entity mapping performance without fine-tuning. The translation-enhancing strategy is applicable to other languages that face the similar challenge due to the absence of well-developed medical terminology systems.

Mapping Chinese Medical Entities to the Unified Medical Language System.

Background: Chinese medical entities have not been organized comprehensively due to the lack of well-developed terminology systems, which poses a challenge to processing Chinese medical texts for fine-grained medical knowledge representation. To unify Chinese medical terminologies, mapping Chinese medical entities to their English counterparts in the Unified Medical Language System (UMLS) is an efficient solution. However, their mappings have not been investigated sufficiently in former research. In this study, we explore strategies for mapping Chinese medical entities to the UMLS and systematically evaluate the mapping performance. Methods: First, Chinese medical entities are translated to English using multiple web-based translation engines. Then, 3 mapping strategies are investigated: (a) string-based, (b) semantic-based, and (c) string and semantic similarity combined. In addition, cross-lingual pretrained language models are applied to map Chinese medical entities to UMLS concepts without translation. All of these strategies are evaluated on the ICD10-CN, Chinese Human Phenotype Ontology (CHPO), and RealWorld datasets. Results: The linear combination method based on the SapBERT and term frequency-inverse document frequency bag-of-words models perform the best on all evaluation datasets, with 91.85%, 82.44%, and 78.43% of the top 5 accuracies on the ICD10-CN, CHPO, and RealWorld datasets, respectively. Conclusions: In our study, we explore strategies for mapping Chinese medical entities to the UMLS and identify a satisfactory linear combination method. Our investigation will facilitate Chinese medical entity normalization and inspire research that focuses on Chinese medical ontology development.

Recent advance of small-molecule drugs for clinical treatment of osteoporosis: A review.

Osteoporosis is a metabolic bone disorder typified by a reduction in bone mass and structural degradation of bone tissue, leading to heightened fragility and vulnerability to fractures. The incidence of osteoporosis increases with age, making it a significant public health challenge. The pathogenesis of osteoporosis involves an imbalance between osteoblast-mediated bone formation and resorption. The current treatment options for osteoporosis include bisphosphonates, hormone replacement therapy (HRT), selective estrogen receptor modulators (SERMs), and denosumab. The recent advances in small-molecule drugs for the clinical treatment of osteoporosis offer promising options for improving bone health and reducing fracture risk. This review aims to provide an overview of the clinical applications and synthetic routes of representative small-molecule drugs for the treatment of osteoporosis. A comprehensive understanding of the synthetic methods of drug molecules for osteoporosis may inspire the development of new, more effective, and practical synthetic techniques for treating this condition.

Lrp10 suppresses IL7R limiting CD8 T cell homeostatic expansion and anti-tumor immunity.

Signals emanating from the T cell receptor (TCR), co-stimulatory receptors, and cytokine receptors each influence CD8 T cell fate. Understanding how these signals respond to homeostatic and microenvironmental cues can reveal new ways to therapeutically direct T cell function. Through forward genetic screening in mice, we discovered that loss-of-function mutations in LDL receptor related protein 10 ( Lrp10 ) caused naïve and central memory CD8 T cells to accumulate in peripheral lymphoid organs. Lrp10 encodes a conserved cell surface protein of unknown immunological function. Lrp10 was induced with T cell activation and its expression post-translationally suppressed IL7 receptor (IL7R) levels. Accordingly, Lrp10 deletion enhanced T cell homeostatic expansion through IL7R signaling. Lrp10 -deficient mice were also intrinsically resistant to syngeneic tumors. This phenotype depended on dense tumor infiltration of CD8 T cells that displayed increased memory cell characteristics, reduced terminal exhaustion, and augmented responses to immune checkpoint inhibition. Here, we present Lrp10 as a new negative regulator of CD8 T cell homeostasis and a host factor that controls tumor resistance with implications for immunotherapy.