PhenoApt leverages clinical expertise to prioritize candidate genes via machine learning.

In recent years, exome sequencing (ES) has shown great utility in the diagnoses of Mendelian disorders. However, after rigorous filtering, a typical ES analysis still involves the interpretation of hundreds of variants, which greatly hinders the rapid identification of causative genes. Since the interpretations of ES data require comprehensive clinical analyses, taking clinical expertise into consideration can speed the molecular diagnoses of Mendelian disorders. To leverage clinical expertise to prioritize candidate genes, we developed PhenoApt, a phenotype-driven gene prioritization tool that allows users to assign a customized weight to each phenotype, via a machine-learning algorithm. Using the ability to rank causative genes in top-10 lists as an evaluation metric, baseline analysis demonstrated that PhenoApt outperformed previous phenotype-driven gene prioritization tools by a relative increase of 22.7%-140.0% in three independent, real-world, multi-center cohorts (cohort 1, n = 185; cohort 2, n = 784; and cohort 3, n = 208). Additional trials showed that, by adding weights to clinical indications, which should be explained by the causative gene, PhenoApt performance was improved by a relative increase of 37.3% in cohort 2 (n = 471) and 21.4% in cohort 3 (n = 208). Moreover, PhenoApt could assign an intrinsic weight to each phenotype based on the likelihood of its being a Mendelian trait using term frequency-inverse document frequency techniques. When clinical indications were assigned with intrinsic weights, PhenoApt performance was improved by a relative increase of 23.7% in cohort 2 and 15.5% in cohort 3. For the integration of PhenoApt into clinical practice, we developed a user-friendly website and a command-line tool.

Comparative transcriptome analysis reveals the redirection of metabolic flux from cell growth to astaxanthin biosynthesis in Yarrowia lipolytica.

Engineering Yarrowia lipolytica to produce astaxanthin provides a promising route. Here, Y. lipolytica M2 producing a titer of 181 mg/L astaxanthin was isolated by iterative atmospheric and room-temperature plasma mutagenesis and diphenylamine-mediated screening. Interestingly, a negative correlation was observed between cell biomass and astaxanthin production. To reveal the underlying mechanism, RNA-seq analysis of transcriptional changes was performed in high producer M2 and reference strain M1, and a total of 1379 differentially expressed genes were obtained. Data analysis revealed that carbon flux was elevated through lipid metabolism, acetyl-CoA and mevalonate supply, but restrained through central carbon metabolism in strain M2. Moreover, upregulation of other pathways such as ATP-binding cassette transporter and thiamine pyrophosphate possibly provided more cofactors for carotenoid hydroxylase and relieved cell membrane stress caused by astaxanthin insertion. These results suggest that balancing cell growth and astaxanthin production may be important to promote efficient biosynthesis of astaxanthin in Y. lipolytica.

Quantification and discovery of quality markers from Toddalia asiatica by UHPLC-MS/MS coupled with chemometrics.

INTRODUCTION: Toddalia asiatica (TA) is a classical traditional Chinese medicine used to treat rheumatoid arthritis and contusions. However, research regarding TA quality control is currently limited. OBJECTIVE: We aimed to establish a strategy for identifying quality markers that can be used for the evaluation of the quality of TA. METHOD: A rapid and efficient ultra-high-performance liquid chromatography coupled with triple quadrupole tandem mass spectrometry (UHPLC-MS/MS) method was developed for the quantitative determination of 19 compounds in TA from different regions. Then, the extraction process of TA was successively optimized by single-factor optimization and response surface methodology. Moreover, chemometrics was employed to confirm the correlation between quality and target compounds. RESULTS: Utilizing the UHPLC-MS/MS method, separation of the 19 bioactive compounds was achieved within 14 min. The method was validated in terms of linearity (r2 > 0.9982), precision (0.08%-3.70%), repeatability (0.50%-2.54%), stability (2.26%-5.46%), and recovery (95.8%-113%). The optimal extraction process (extraction solvent, 65% ethanol aqueous solution; solid-liquid ratio, 1:20; extraction time, 25 min) was determined with the total content of 19 bioactive compounds as indicator. Significant disparities were observed in the contents of target compounds across different batches of TA. Besides, all samples could be categorized into two distinct groups, and magnoflorine, (-)-lyoniresinol, nitidine chloride, norbraylin, skimmianine, and decarine were identified as quality markers. CONCLUSION: In the present study, we developed a strategy to improve the quality control of TA. In consideration of the pharmacodynamic activity and statistical differences, six compounds are proposed as quality markers for TA.

USF1-mediated ALKBH5 stabilizes FLII mRNA in an m6A-YTHDF2-dependent manner to repress glycolytic activity in prostate adenocarcinoma.

Upstream-stimulating factor 1 (USF1) is a ubiquitously expressed transcription factor implicated in multiple cellular processes, including metabolism and proliferation. This study focused on the function of USF1 in glycolysis and the malignant development of prostate adenocarcinoma (PRAD). Bioinformatics predictions suggested that USF1 is poorly expressed in PRAD. The clinical PRAD samples revealed a low level of USF1, which was correlated with an unfavorable prognosis. Artificial upregulation of USF1 significantly repressed glycolytic activity in PRAD cells and reduced cell growth and metastasis in vitro and in vivo. Potential downstream genes of USF1 were probed by integrated bioinformatics analyses. The chromatin immunoprecipitation and luciferase assays indicated that USF1 bound to the α-ketoglutarate-dependent dioxygenase alkB homolog 5 (ALKBH5) promoter for transcription activation. Flightless I (FLII) was identified as the gene showing the highest degree of correlation with ALKBH5. As an m6A demethylase, ALKBH5 enhanced FLII mRNA stability by inducing m6A demethylation in an m6A-YTH N6-methyladenosine RNA-binding protein F2 (YTHDF2)-dependent manner. Either silencing of ALKBH5 or FLII blocked the role of USF1 in PARD cells and restored glycolysis, cell proliferation, and invasion. This study demonstrates that USF1 activates ALKBH5 to stabilize FLII mRNA in an m6A-YTHDF2-dependent manner, thereby repressing glycolysis processes and the progression of PRAD.

IRE1α-XBP1 regulates PDK1-dependent induction of epithelial-mesenchymal transition in non-small cell lung cancer cells.

Mounting evidence indicates that activation of unfolded protein response (UPR) and metabolic reprogramming contribute to cancer cell migration and invasion, but the molecular mechanism of pro-EMT program through a coordinated action of UPR with metabolism has not been defined. In this study, we utilized ER stress-inducing reagent, thapsigargin (TG), to induced pharmacologic ER stress in lung cancer cells. Here. We report that the branch of UPR, IRE1α-XBP1 pathway plays a pivotal role in reprogramming lung cancer cell metabolism. At the molecular level, the expression of pyruvate dehydrogenase kinase-1 (PDK-1) is directly induced by XBP1 as a consequence of UPR activation, thus facilitating aerobic glycolysis and lactate production. We also demonstrated that PDK1 serves as a downstream element of UPR activation in induction of Snail and EMT program. In addition, PDK1-induced Snail was dependent on the lactate production derived from metabolic reprogramming. Our findings reveal a critical role of lactate in pro-invasion events and establishes a direct connection between ER-stress and metabolic reprogramming in facilitating cancer cell progression.

Orexin-A Intensifies Mouse Pupillary Light Response by Modulating Intrinsically Photosensitive Retinal Ganglion Cells.

We show for the first time that the neuropeptide orexin modulates pupillary light response, a non-image-forming visual function, in mice of either sex. Intravitreal injection of the orexin receptor (OXR) antagonist TCS1102 and orexin-A reduced and enhanced pupillary constriction in response to light, respectively. Orexin-A activated OX1Rs on M2-type intrinsically photosensitive retinal ganglion cells (M2 cells), and caused membrane depolarization of these cells by modulating inward rectifier potassium channels and nonselective cation channels, thus resulting in an increase in intrinsic excitability. The increased intrinsic excitability could account for the orexin-A-evoked increase in spontaneous discharges and light-induced spiking rates of M2 cells, leading to an intensification of pupillary constriction. Orexin-A did not alter the light response of M1 cells, which could be because of no or weak expression of OX1Rs on them, as revealed by RNAscope in situ hybridization. In sum, orexin-A is likely to decrease the pupil size of mice by influencing M2 cells, thereby improving visual performance in awake mice via enhancing the focal depth of the eye's refractive system.SIGNIFICANCE STATEMENT This study reveals the role of the neuropeptide orexin in mouse pupillary light response, a non-image-forming visual function. Intravitreal orexin-A administration intensifies light-induced pupillary constriction via increasing the excitability of M2 intrinsically photosensitive retinal ganglion cells by activating the orexin receptor subtype OX1R. Modulation of inward rectifier potassium channels and nonselective cation channels were both involved in the ionic mechanisms underlying such intensification. Orexin could improve visual performance in awake mice by reducing the pupil size and thereby enhancing the focal depth of the eye's refractive system.

Multifunctional role of a fungal pathogen-secreted laccase 2 in evasion of insect immune defense.

Laccases are widely present in bacteria, fungi, plants and invertebrates and involved in a variety of physiological functions. Here, we report that Beauveria bassiana, an economic important entomopathogenic fungus, secretes a laccase 2 (BbLac2) during infection that detoxifies insect immune response-generated reactive oxygen species (ROS) and interferes with host immune phenoloxidase (PO) activation. BbLac2 is expressed in fungal cells during proliferation in the insect haemocoel and can be found to distribute on the surface of haemolymph-derived in vivo fungal hyphal bodies or be secreted. Targeted gene-knockout of BbLac2 increased fungal sensitivity to oxidative stress, decreased virulence to insect, and increased host PO activity. Strains overexpressing BbLac2 showed increased virulence, with reduced host PO activity and lowered ROS levels in infected insects. In vitro assays revealed that BbLac2 could eliminate ROS and oxidize PO substrates (phenols), verifying the enzymatic functioning of the protein in detoxification of cytotoxic ROS and interference with the PO cascade. Moreover, BbLac2 acted as a cell surface protein that masked pathogen associated molecular patterns (PAMPs), enabling the pathogen to evade immune recognition. Our data suggest a multifunctional role for fungal pathogen-secreted laccase 2 in evasion of insect immune defenses.

Factors and predictive model associated with perioperative complications after long fusion in the treatment of adult non-degenerative scoliosis.

INTRODUCTION: Adult non-degenerative scoliosis accounts for 90% of spinal deformities in young adults. However, perioperative complications and related risk factors of long posterior instrumentation and fusion for the treatment of adult non-degenerative scoliosis have not been adequately studied. METHODS: We evaluated clinical and radiographical results from 146 patients with adult non-degenerative scoliosis who underwent long posterior instrumentation and fusion. Preoperative clinical data, intraoperative variables, and perioperative radiographic parameters were collected to analyze the risk factors for perioperative complications. Potential and independent risk factors for perioperative complications were evaluated by univariate analysis and logistic regression analysis. RESULTS: One hundred forty-six adult non-degenerative scoliosis patients were included in our study. There were 23 perioperative complications for 21 (14.4%) patients, eight of which were cardiopulmonary complications, two of which were infection, six of which were neurological complications, three of which were gastrointestinal complications, and four of which were incision-related complication. The independent risk factors for development of total perioperative complications included change in Cobb angle (odds ratio [OR] = 1.085, 95% CI = 1.035 ~ 1.137, P = 0.001) and spinal osteotomy (OR = 3.565, 95% CI = 1.039 ~ 12.236, P = 0.043). The independent risk factor for minor perioperative complications is change in Cobb angle (OR = 1.092, 95% CI = 1.023 ~ 1.165, P = 0.008). The independent risk factors for major perioperative complications are spinal osteotomy (OR = 4.475, 95% CI = 1.960 ~ 20.861, P = 0.036) and change in Cobb angle (OR = 1.106, 95% CI = 1.035 ~ 1.182, P = 0.003). CONCLUSIONS: Our study indicate that change in Cobb angle and spinal osteotomy are independent risk factors for total perioperative complications after long-segment posterior instrumentation and fusion in adult non-degenerative scoliosis patients. Change in Cobb angle is an independent risk factor for minor perioperative complications. Change in Cobb angle and spinal osteotomy are independent risk factors for major perioperative complications.

Lactate-fueled oxidative metabolism drives DNA methyltransferase 1-mediated transcriptional co-activator with PDZ binding domain protein activation.

Activity of transcriptional co-activator with PDZ binding domain (TAZ) protein is strongly implicated in the pathogenesis of human cancer and is influenced by tumor metabolism. High levels of lactate concentration in the tumor microenvironment as a result of metabolic reprogramming are inversely correlated with patient overall survival. Herein, we investigated the role of lactate in the regulation of the activity of TAZ and showed that glycolysis-derived lactate efficiently increased TAZ expression and activity in lung cancer cells. We showed that the reactive oxygen species (ROS) generated by lactate-fueled oxidative phosphorylation (OXPHOS) in mitochondria activated AKT and thereby inhibited glycogen synthase kinase 3 beta/beta-transducin repeat-containing proteins (GSK-3ß/ß-TrCP)-mediated ubiquitination and degradation of DNA methyltransferase 1 (DNMT1). Upregulation of DNMT1 by lactate caused hypermethylation of TAZ negative regulator of the LATS2 gene promoter, leading to TAZ activation. Moreover, TAZ binds to the promoter of DNMT1 and is necessary for DNMT1 transcription. Our study showed a molecular mechanism of DNMT1 in linking tumor metabolic reprogramming to the Hippo-TAZ pathway and functional significance of the DNMT1-TAZ feedback loop in the migratory and invasive potential of lung cancer cells.

A novel COMP mutation in a Chinese family with multiple epiphyseal dysplasia.

BACKGROUND: Multiple epiphyseal dysplasia (MED) is a skeletal disorder characterized by delayed and irregular ossification of the epiphyses and early-onset osteoarthritis. At least 66% of the reported autosomal dominant MED (AD-MED) cases are caused by COMP mutations. METHODS: We recruited a four-generation Chinese family with early-onset hip osteoarthritis, flatfoot, brachydactyly, and mild short stature. An assessment of the family history, detailed physical examinations, and radiographic evaluations were performed on the proband and other family members, followed by the performance of whole-exome sequencing (WES). The pathogenicity of the candidate mutation was also analyzed. RESULTS: An AD-MED family with 10 affected members and 17 unaffected members was recruited. The main radiographic findings were symmetrical changes in the dysplastic acetabulum and femoral heads, irregular contours of the epiphyses, a shortened femoral neck, and flatfoot. Lower bone density was also observed in the ankle joints, wrist joints, and knees, as well as irregular vertebral end plates. In the proband, we identified the missense mutation c.1153G > T (p. Asp385Tyr), located in exon 11 of the COMP gene. This mutation was assessed as 'pathogenic' because of its low allele frequency and its high likelihood of co-segregation with disease in the reported family. Sanger sequencing validated the novel heterozygous mutation c.1153G > T (p. Asp385Tyr) in exon 11 of COMP in all affected individuals in the family. CONCLUSIONS: Our results underlined a key role of the Asp385 amino acid in the protein function of COMP and confirmed the pathogenicity of the COMP (c.1153G > T; p. Asp385Tyr) mutation in AD-MED disease. We have therefore expanded the known mutational spectrum of COMP and revealed new phenotypic information for AD-MED.

Identification of novel FBN1 variations implicated in congenital scoliosis.

Congenital scoliosis (CS) is a form of scoliosis caused by congenital vertebral malformations. Genetic predisposition has been demonstrated in CS. We previously reported that TBX6 loss-of-function causes CS in a compound heterozygous model; however, this model can explain only 10% of CS. Many monogenic and polygenic CS genes remain to be elucidated. In this study, we analyzed exome sequencing (ES) data of 615 Chinese CS from the Deciphering Disorders Involving Scoliosis and COmorbidities (DISCO) project. Cosegregation studies for 103 familial CS identified a novel heterozygous nonsense variant, c.2649G>A (p.Trp883Ter) in FBN1. The association between FBN1 and CS was then analyzed by extracting FBN1 variants from ES data of 574 sporadic CS and 828 controls; 30 novel variants were identified and prioritized for further analyses. A mutational burden test showed that the deleterious FBN1 variants were significantly enriched in CS subjects (OR = 3.9, P = 0.03 by Fisher's exact test). One missense variant, c.2613A>C (p.Leu871Phe) was recurrent in two unrelated CS subjects, and in vitro functional experiments for the variant suggest that FBN1 may contribute to CS by upregulating the transforming growth factor beta (TGF-ß) signaling. Our study expanded the phenotypic spectrum of FBN1, and provided nove insights into the genetic etiology of CS.

Clinicopathological characteristics, treatment and prognosis of head & neck small cell carcinoma: a SEER population-based study.

BACKGROUND: To investigate the clinicopathological characteristics of head and neck small cell carcinoma (H&NSmCC) and identify prognostic factors on the basis of the Surveillance, Epidemiology and End Results (SEER) database. METHODS: Total of 789 primary cases from 1973 to 2016 were included. Univariate and multivariate analyses were performed to identify independent prognostic indicators. An H&NSmCC-specific nomogram was constructed and compared with the AJCC staging system by calculating the time-dependent area under the curve (AUC) of the receiver operating characteristic (ROC) curves. RESULTS: The incidence of H&NSmCC peaked during the period of 50 to 70 years old, and the most frequent location was the salivary gland. The 5-year disease specific survival (DSS) was 27%. In the multivariate survival analysis, AJCC III + IV stage [HR = 2.5, P = 0.03, I + II stage as Ref], positive N stage [HR = 1.67, P = 0.05, negative N stage as Ref], positive M stage [HR = 4.12, P = 0.000, negative M stage as Ref] and without chemotherapy [HR = 0.56, P = 0.023, received chemotherapy as Ref] were independently associated with DSS. The H&NSmCC-specific nomogram was built based on the independent prognostic indicators. The nomogram demonstrated better predictive capacity than the AJCC staging system for 5-year DSS [(AUC: 0.75 vs 0.634; Harrell's C-index (95% CI): 0.7(0.66-0.74) vs 0.59(0.55-0.62), P < 0.05]. CONCLUSION: N stage, M stage, AJCC stage and chemotherapy were independent prognostic indicators included in the prognostic nomogram model, which can better predict the survival of H&NSmCC than the AJCC staging system.

Malignant tumours of temporomandibular joint.

BACKGROUND: Malignant tumours of the temporomandibular joint (MTTMJ) are extremely rare. Studies describing its unique epidemiology, clinicopathological features, treatment and prognosis comprehensively are limited. To address these issues, current investigation was performed. METHODS: A retrospective research was carried out by using population-based data from the Surveillance, Epidemiology, and End Results database (1973-2016). RESULTS: Data for a total of 734 patients, including 376 men and 358 women, was found. The median age was 47 years. The 5-year and 10-year disease specific survival (DSS) rates were 69.2 and 63.6%, respectively. Significant differences in DSS were found according to age, race, tumour type, AJCC/TNM stage, surgery, radiotherapy, chemotherapy and different treatment modalities (P < 0.05). In the multivariate survival analysis, age > 44 years and AJCC stage III and IV were associated with poor DSS. CONCLUSION: MTTMJ was mostly found in white people with a median age of 47 years without any sex predominance. Patient's age and AJCC stage was independent predictor of DSS.

Bridging Dealumination and Desilication for the Synthesis of Hierarchical MFI Zeolites.

The rational design of zeolite-based catalysts calls for flexible tailoring of porosity and acidity beyond micropore dimension. To date, dealumination has been applied extensively as an industrial technology for the tailoring of zeolite in micropore dimension, whereas desilication has separately shown its potentials in the creation of mesoporosities. The free coupling of dealumination with desilication will bridge the tailoring at micro/mesopore dimensions; however, such coupling has been prevailingly confirmed as an impossible mission. In this work, a consecutive dealumination-desilication process enables the introduction of uniform intracrystalline mesopores (4-6 nm) into the microporous Al-rich zeolites. The decisive impacts of steaming step have been firstly discovered. These findings revitalize the functions of dealumination in porosity tailoring, and stimulate the pursuit of new methods for the tailoring of industrially relevant Al-rich zeolites.

Identification of Diagnostic Genes of Aortic Stenosis That Progresses from Aortic Valve Sclerosis.

Background: Aortic valve sclerosis (AVS) is a pathological state that can progress to aortic stenosis (AS), which is a high-mortality valvular disease. However, effective medical therapies are not available to prevent this progression. This study aimed to explore potential biomarkers of AVS-AS advancement. Methods: A microarray dataset and an RNA-sequencing dataset were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were screened from AS and AVS samples. Functional enrichment analysis, protein-protein interaction (PPI) network construction, and machine learning model construction were conducted to identify diagnostic genes. A receiver operating characteristic (ROC) curve was generated to evaluate diagnostic value. Immune cell infiltration was then used to analyze differences in immune cell proportion between tissues. Finally, immunohistochemistry was applied to further verify protein concentration of diagnostic factors. Results: A total of 330 DEGs were identified, including 92 downregulated and 238 upregulated genes. The top 5% of DEGs (n = 17) were screened following construction of a PPI network. IL-7 and VCAM-1 were identified as the most significant candidate genes via least absolute shrinkage and selection operator (LASSO) regression. The diagnostic value of the model and each gene were above 0.75. Proportion of anti-inflammatory M2 macrophages was lower, but the fraction of pro-inflammatory gamma-delta T cells was elevated in AS samples. Finally, levels of IL-7 and VCAM-1 were validated to be higher in AS tissue than in AVS tissue using immunohistochemistry. Conclusion: IL-7 and VCAM-1 were identified as biomarkers during the disease progression. This is the first study to analyze gene expression differences between AVS and AS and could open novel sights for future studies on alleviating or preventing the disease progression.

Identification of pyroptosis-associated genes with diagnostic value in calcific aortic valve disease.

Background: Calcific aortic valve disease (CAVD) is one of the most prevalent valvular diseases and is the second most common cause for cardiac surgery. However, the mechanism of CAVD remains unclear. This study aimed to investigate the role of pyroptosis-related genes in CAVD by performing comprehensive bioinformatics analysis. Methods: Three microarray datasets (GSE51472, GSE12644 and GSE83453) and one RNA sequencing dataset (GSE153555) were obtained from the Gene Expression Omnibus (GEO) database. Pyroptosis-related differentially expressed genes (DEGs) were identified between the calcified and the normal valve samples. LASSO regression and random forest (RF) machine learning analyses were performed to identify pyroptosis-related DEGs with diagnostic value. A diagnostic model was constructed with the diagnostic candidate pyroptosis-related DEGs. Receiver operating characteristic (ROC) curve analysis was performed to estimate the diagnostic performances of the diagnostic model and the individual diagnostic candidate genes in the training and validation cohorts. CIBERSORT analysis was performed to estimate the differences in the infiltration of the immune cell types. Pearson correlation analysis was used to investigate associations between the diagnostic biomarkers and the immune cell types. Immunohistochemistry was used to validate protein concentration. Results: We identified 805 DEGs, including 319 down-regulated genes and 486 up-regulated genes. These DEGs were mainly enriched in pathways related to the inflammatory responses. Subsequently, we identified 17 pyroptosis-related DEGs by comparing the 805 DEGs with the 223 pyroptosis-related genes. LASSO regression and RF algorithm analyses identified three CAVD diagnostic candidate genes (TREM1, TNFRSF11B, and PGF), which were significantly upregulated in the CAVD tissue samples. A diagnostic model was constructed with these 3 diagnostic candidate genes. The diagnostic model and the 3 diagnostic candidate genes showed good diagnostic performances with AUC values >0.75 in both the training and the validation cohorts based on the ROC curve analyses. CIBERSORT analyses demonstrated positive correlation between the proportion of M0 macrophages in the valve tissues and the expression levels of TREM1, TNFRSF11B, and PGF. Conclusion: Three pyroptosis-related genes (TREM1, TNFRSF11B and PGF) were identified as diagnostic biomarkers for CAVD. These pyroptosis genes and the pro-inflammatory microenvironment in the calcified valve tissues are potential therapeutic targets for alleviating CAVD.

Empowering Low-Temperature Lithium-Sulfur Batteries: Unlocking the Potential of Transition Metal Alloy-Based Cathode Materials.

At low temperatures, lithium-sulfur (Li-S) batteries have poor kinetics, resulting in extreme polarization and decreased capacity. In this study, we investigated the electrochemical performance of Li-S batteries utilizing transition metal alloy-based cathode materials. Specifically, binary transition metal alloys (FeNi, FeCo, and NiCo) are integrated into a porous carbon nanofiber (CNF) matrix as composite cathode material. Our findings reveal that alloying metallic Ni with Fe in the FeNi@CNFs composite enhances the catalytic conversion of sulfur species, mitigating the shuttle effect and improving battery performance even under low temperatures. Li-S batteries employing a Li2S6/FeNi@CNFs cathode exhibited a significantly high initial discharge capacity of 1655 mAh g-1 at 0.1 C. Even at the higher current density of 10 C, the Li2S6/FeNi@CNFs composite can still reach an ultrahigh specific capacity of 828 mAh g-1. In addition, Li2S6/FeNi@CNFs demonstrated exceptional initial discharge capacities of 890.5 and 382.7 mAh g-1 at 0.1 C under -20 and -40 °C, respectively. With an initial capacity of 392.02 mAh g-1 and a capacity retention rate of 88.86% (after 60 cycles) at 0.2 C, the conversion of LiPSs in Li2S6/FeNi@CNFs is significantly enhanced even at ultralow temperatures of -40 °C. The findings of this study hold significant implications for the advancement of extremely low-temperature Li-S batteries.

Deciphering the pathogenic role of rare RAF1 heterozygous missense mutation in the late-presenting DDH.

Background: Developmental Dysplasia of the Hip (DDH) is a skeletal disorder where late-presenting forms often escape early diagnosis, leading to limb and pain in adults. The genetic basis of DDH is not fully understood despite known genetic predispositions. Methods: We employed Whole Genome Sequencing (WGS) to explore the genetic factors in late-presenting DDH in two unrelated families, supported by phenotypic analyses and in vitro validation. Results: In both cases, a novel de novo heterozygous missense mutation in RAF1 (c.193A>G [p.Lys65Glu]) was identified. This mutation impacted RAF1 protein structure and function, altering downstream signaling in the Ras/ERK pathway, as demonstrated by bioinformatics, molecular dynamics simulations, and in vitro validations. Conclusion: This study contributes to our understanding of the genetic factors involved in DDH by identifying a novel mutation in RAF1. The identification of the RAF1 mutation suggests a possible involvement of the Ras/ERK pathway in the pathogenesis of late-presenting DDH, indicating its potential role in skeletal development.

Copolymer Brush Particle Hybrid Materials with "Recall-and-Repair" Capability.

The effect of sequence structure on the self-healing and shape-memory properties of copolymer-tethered brush particle films was investigated and compared to linear copolymer analogs. Poly(n-butyl acrylate-co-methyl methacrylate), P(BA-co-MMA), and linear and brush analogs with controlled gradient and statistical sequence were synthesized by atom transfer radical polymerization (ATRP). The effect of sequence on self-healing in BA/MMA copolymer brush particle hybrids followed similar trends as for linear analogs. Most rapid restoration of mechanical properties was found for statistical copolymer sequence; an increase of the high Tg (MMA) component provided a path to raise the material's modulus while retaining self-heal ability. Creep testing revealed profound differences between linear and brush systems. While linear copolymers featured substantial viscous deformation when exposed to constant stress in the linear regime, brush analogs displayed minimal permanent deformation and featured shape restoration. The reduction of flow was interpreted to be a consequence of slow cooperative relaxation due to the complex microstructure of brush particle hybrids in which long-range motions are constrained through entanglements and slow-diffusing particle cores. The rubbery-like response imparts BA/MMA copolymer brush material systems concurrent "shape-memory" and "self-heal" capability. This ability to "recall-and-repair" could find application in the design of functional hybrid materials, for example, for soft robotics.

SpineHRformer: A Transformer-Based Deep Learning Model for Automatic Spine Deformity Assessment with Prospective Validation.

The Cobb angle (CA) serves as the principal method for assessing spinal deformity, but manual measurements of the CA are time-consuming and susceptible to inter- and intra-observer variability. While learning-based methods, such as SpineHRNet+, have demonstrated potential in automating CA measurement, their accuracy can be influenced by the severity of spinal deformity, image quality, relative position of rib and vertebrae, etc. Our aim is to create a reliable learning-based approach that provides consistent and highly accurate measurements of the CA from posteroanterior (PA) X-rays, surpassing the state-of-the-art method. To accomplish this, we introduce SpineHRformer, which identifies anatomical landmarks, including the vertices of endplates from the 7th cervical vertebra (C7) to the 5th lumbar vertebra (L5) and the end vertebrae with different output heads, enabling the calculation of CAs. Within our SpineHRformer, a backbone HRNet first extracts multi-scale features from the input X-ray, while transformer blocks extract local and global features from the HRNet outputs. Subsequently, an output head to generate heatmaps of the endplate landmarks or end vertebra landmarks facilitates the computation of CAs. We used a dataset of 1934 PA X-rays with diverse degrees of spinal deformity and image quality, following an 8:2 ratio to train and test the model. The experimental results indicate that SpineHRformer outperforms SpineHRNet+ in landmark detection (Mean Euclidean Distance: 2.47 pixels vs. 2.74 pixels), CA prediction (Pearson correlation coefficient: 0.86 vs. 0.83), and severity grading (sensitivity: normal-mild; 0.93 vs. 0.74, moderate; 0.74 vs. 0.77, severe; 0.74 vs. 0.7). Our approach demonstrates greater robustness and accuracy compared to SpineHRNet+, offering substantial potential for improving the efficiency and reliability of CA measurements in clinical settings.