Strategies in product engineering of mesenchymal stem cell-derived exosomes: unveiling the mechanisms underpinning the promotive effects of mesenchymal stem cell-derived exosomes.

Articular cartilage injuries present a significant global challenge, particularly in the aging population. These injuries not only restrict movement due to primary damage but also exacerbate elderly degenerative lesions, leading to secondary cartilage injury and osteoarthritis. Addressing osteoarthritis and cartilage damage involves overcoming several technical challenges in biological treatment. The use of induced mesenchymal stem cells (iMSCs) with functional gene modifications emerges as a solution, providing a more stable and controllable source of Mesenchymal Stem Cells (MSCs) with reduced heterogeneity. Furthermore, In addition, this review encompasses strategies aimed at enhancing exosome efficacy, comprising the cultivation of MSCs in three-dimensional matrices, augmentation of functional constituents within MSC-derived exosomes, and modification of their surface characteristics. Finally, we delve into the mechanisms through which MSC-exosomes, sourced from diverse tissues, thwart osteoarthritis (OA) progression and facilitate cartilage repair. This review lays a foundational framework for engineering iMSC-exosomes treatment of patients suffering from osteoarthritis and articular cartilage injuries, highlighting cutting-edge research and potential therapeutic pathways.

Development and validation of a novel nomogram for predicting good neoangiogenesis after encephaloduroarteriosynangiosis in patients with moyamoya disease and type 2 diabetes mellitus: a case-control study.

OBJECTIVE: Diabetes is often linked to poorer outcomes in patients with moyamoya disease (MMD). However, experience has shown that certain individuals with diabetes have favorable outcomes after encephaloduroarteriosynangiosis (EDAS). The authors aimed to develop a nomogram to predict good neoangiogenesis in patients with MMD and type 2 diabetes mellitus (T2DM) to aid neurosurgeons in the identification of suitable candidates for EDAS. METHODS: Adults with MMD and T2DM who underwent EDAS between June 2004 and December 2018 were included in the analysis. In total, 126 patients (213 hemispheres) with MMD and T2DM from the Fifth Medical Centre of the Chinese PLA General Hospital were included and randomly divided into training (152 hemispheres) and internal validation (61 hemispheres) cohorts at a ratio of 7:3. Univariate logistic and least absolute shrinkage and selection operator regression analyses were used to identify the significant factors associated with good neoangiogenesis, which were used to develop a nomogram. The discrimination, calibration, and clinical utility were assessed. RESULTS: A total of 213 hemispheres in 126 patients were reviewed, including 152 (71.36%) hemispheres with good postoperative collateral formation and 61 (28.64%) with poor postoperative collateral formation. The authors selected 4 predictors (FGD5 rs11128722, VEGFA rs9472135, Suzuki stage, and internal carotid artery [ICA] moyamoya vessels) for nomogram development. The C-indices of the nomogram in the training and internal validation cohorts were 0.873 and 0.841, respectively. The nomogram exhibited a sensitivity of 84.5% and specificity of 81.0%. The positive and negative predictive values were 92.1% and 66.7%, respectively. The calibration curves indicated high predictive accuracy, and receiver operating characteristic curve analysis showed the superiority of the nomogram. The decision-making analysis validated the fitness and clinical application value of this nomogram. Then a web-based calculator to facilitate clinical application was generated. CONCLUSIONS: The nomogram developed in this study accurately predicted neoangiogenesis in patients with MMD and T2DM after EDAS and may assist neurosurgeons in identifying suitable candidates for indirect revascularization surgery.

Restoration of HMGCS2-mediated ketogenesis alleviates tacrolimus-induced hepatic lipid metabolism disorder.

Tacrolimus, one of the macrolide calcineurin inhibitors, is the most frequently used immunosuppressant after transplantation. Long-term administration of tacrolimus leads to dyslipidemia and affects liver lipid metabolism. In this study, we investigated the mode of action and underlying mechanisms of this adverse reaction. Mice were administered tacrolimus (2.5 mg·kg-1·d-1, i.g.) for 10 weeks, then euthanized; the blood samples and liver tissues were collected for analyses. We showed that tacrolimus administration induced significant dyslipidemia and lipid deposition in mouse liver. Dyslipidemia was also observed in heart or kidney transplantation patients treated with tacrolimus. We demonstrated that tacrolimus did not directly induce de novo synthesis of fatty acids, but markedly decreased fatty acid oxidation (FAO) in AML12 cells. Furthermore, we showed that tacrolimus dramatically decreased the expression of HMGCS2, the rate-limiting enzyme of ketogenesis, with decreased ketogenesis in AML12 cells, which was responsible for lipid deposition in normal hepatocytes. Moreover, we revealed that tacrolimus inhibited forkhead box protein O1 (FoxO1) nuclear translocation by promoting FKBP51-FoxO1 complex formation, thus reducing FoxO1 binding to the HMGCS2 promoter and its transcription ability in AML12 cells. The loss of HMGCS2 induced by tacrolimus caused decreased ketogenesis and increased acetyl-CoA accumulation, which promoted mitochondrial protein acetylation, thereby resulting in FAO function inhibition. Liver-specific HMGCS2 overexpression via tail intravenous injection of AAV8-TBG-HMGCS2 construct reversed tacrolimus-induced mitochondrial protein acetylation and FAO inhibition, thus removing the lipid deposition in hepatocytes. Collectively, this study demonstrates a novel mechanism of liver lipid deposition and hyperlipidemia induced by long-term administration of tacrolimus, resulted from the loss of HMGCS2-mediated ketogenesis and subsequent FAO inhibition, providing an alternative target for reversing tacrolimus-induced adverse reaction.

Comprehensive analysis of KLF family reveals KLF6 as a promising prognostic and immune biomarker in pancreatic ductal adenocarcinoma.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest tumors worldwide, with extremely aggressive and complicated biology. Krüppel-like factors (KLFs) encode a series of transcriptional regulatory proteins and play crucial roles in a variety of processes, including tumor cell differentiation and proliferation. However, the potential biological functions and possible pathways of KLFs in the progression of PDAC remain elusive. METHODS: We systematically evaluated the transcriptional variations and expression patterns of KLFs in pancreatic cancer from the UCSC Xena. Based on difference analysis, the non-negative matrix factorization (NMF) algorithm was utilized to identify the immune characteristics and clinical significance of two different subtypes. The multivariate Cox regression was used to construct the risk model and then explore the differences in tumor immune microenvironment (TIME) and drug sensitivity between high and low groups. Through single-cell RNA sequencing (scRNA-seq) analysis, we screened KLF6 and further investigated its biological functions in pancreatic cancer and pan-cancer. RESULTS: The KLFs exhibited differential expression and mutations in the transcriptomic profile of PDAC. According to the expression of KLFs, patients were classified into two distinct subtypes, each exhibiting significant differences in prognosis and TIME. Moreover, the KLF signature was developed using univariate Cox and Lasso regression, which proved to be a reliable and effective prognostic model. Furthermore, the KLF_Score was closely associated with immune infiltration, response to immunotherapy, and drug sensitivity and we screened small molecule compounds targeting prognostic genes separately. Through scRNA-seq analysis, KLF6 was selected to further demonstrate its role in the malignance of PC in vitro. Finally, pan-cancer analysis emphasized the biological significance of KLF6 in multiple types of tumors and its clinical utility in assessing cancer prognosis. CONCLUSION: This study elucidated the pivotal role of KLF family genes in the malignant development of PC through comprehensive analysis and revealed that KLF6 would be a novel diagnostic biomolecule marker and potential therapeutic target for PDAC.

Coupling High Hardness and Zn Affinity in Amorphous-Crystalline Diamond for Stable Zn Metal Anodes.

The highly reversible plating/stripping of Zn is plagued by dendrite growth and side reactions on metallic Zn anodes, retarding the commercial application of aqueous Zn-ion batteries. Herein, a distinctive nano dual-phase diamond (NDPD) comprised of an amorphous-crystalline heterostructure is developed to regulate Zn deposition and mechanically block dendrite growth. The rich amorphous-crystalline heterointerfaces in the NDPD endow modified Zn anodes with enhanced Zn affinity and result in homogeneous nucleation. In addition, the unparalleled hardness of the NDPD effectively overcomes the high growth stress of dendrites and mechanically impedes their proliferation. Moreover, the hydrophobic surfaces of the NDPD facilitate the desolvation of hydrate Zn2+ and prevent water-mediated side reactions. Consequently, the Zn@NDPD presents an ultrastable lifespan exceeding 3200 h at 5 mA cm-2 and 1 mAh cm-2. The practical application potential of Zn@NDPD is further demonstrated in full cells. This work exhibits the great significance of a chemical-mechanical synergistic anode modification strategy in constructing high-performance aqueous Zn-ion batteries.

Research on emergency logistics information traceability model and resource optimization allocation strategies based on consortium blockchain.

In response to increasingly complex social emergencies, this study realizes the optimization of logistics information flow and resource allocation by constructing the Emergency logistics information Traceability model (ELITM-CBT) based on alliance blockchain technology. Using the decentralized, data immutable and transparent characteristics of alliance blockchain technology, this research breaks through the limitations of traditional emergency logistics models and improves the accuracy and efficiency of information management. Combined with the hybrid genetic simulated Annealing algorithm (HGASA), the improved model shows significant advantages in emergency logistics scenarios, especially in terms of total transportation time, total cost, and fairness of resource allocation. The simulation results verify the high efficiency of the model in terms of timeliness of emergency response and accuracy of resource allocation, and provide innovative theoretical support and practical scheme for the field of emergency logistics. Future research will explore more efficient consensus mechanisms, and combine big data and artificial intelligence technology to further improve the performance and adaptability of emergency logistics systems.

Development and validation of a novel nomogram for predicting long-term rebleeding risk among patients with hemorrhagic moyamoya disease: a 10-year multicenter retrospective cohort study.

OBJECTIVE: The aim of this study was to develop and validate a predictive nomogram model for long-term rebleeding events in patients with hemorrhagic moyamoya disease (HMMD). METHODS: In total, 554 patients with HMMD from the Fifth Medical Center of the Chinese PLA General Hospital (5-PLAGH cohort) were included and randomly divided into training (390 patients) and internal validation (164 patients) sets. An independent cohort from the First Medical Center and Eighth Medical Center of Chinese PLA General Hospital (the 1-PLAGH and 8-PLAGH cohort) was used for external validation (133 patients). Univariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) regression algorithm were used to identify significant factors associated with rebleeding, which were used to develop a nomogram for predicting 5- and 10-year rebleeding. RESULTS: Intraventricular hemorrhage was the most common type of cerebral hemorrhage (39.0% of patients in the 5-PLAGH cohort and 42.9% of the 1-PLAGH and 8-PLAGH cohort). During the mean ± SD follow-up period of 10.4 ± 2.9 years, 91 (16.4%) patients had rebleeding events in the 5-PLAGH cohort. The rebleeding rates were 12.3% (68 patients) at 5 years and 14.8% (82 patients) at 10 years. Rebleeding events were observed in 72 patients (14.3%) in the encephaloduroarteriosynangiosis (EDAS) surgery group, whereas 19 patients (37.3%) experienced rebleeding events in the conservative treatment group. This difference was statistically significant (p < 0.001). We selected 4 predictors (age at onset, number of episodes of bleeding, posterior circulation involvement, and EDAS surgery) for nomogram development. The concordance index (C-index) values of the nomograms of the training cohort, internal validation cohort, and the external validation cohort were 0.767 (95% CI 0.704-0.830), 0.814 (95% CI 0.694-0.934), and 0.718 (95% CI 0.661-0.775), respectively. The nomogram at 5 years exhibited a sensitivity of 48.1% and specificity of 87.5%. The positive and negative predictive values were 38.2% and 91.3%, respectively. The nomogram at 10 years exhibited a sensitivity of 47.1% and specificity of 89.1%. The positive and negative predictive values were 48.5% and 88.5%, respectively. CONCLUSIONS: EDAS may prevent rebleeding events and improve long-term clinical outcomes in patients with HMMD. The nomogram accurately predicted rebleeding events and assisted clinicians in identifying high-risk patients and devising individual treatments. Simultaneously, comprehensive and ongoing monitoring should be implemented for specific patients with HMMD throughout their entire lifespan.

EEG classification model for virtual reality motion sickness based on multi-scale CNN feature correlation.

BACKGROUND: Virtual reality motion sickness (VRMS) is a key issue hindering the development of virtual reality technology, and accurate detection of its occurrence is the first prerequisite for solving the issue. OBJECTIVE: In this paper, a convolutional neural network (CNN) EEG detection model based on multi-scale feature correlation is proposed for detecting VRMS. METHODS: The model uses multi-scale 1D convolutional layers to extract multi-scale temporal features from the multi-lead EEG data, and then calculates the feature correlations of the extracted multi-scale features among all the leads to form the feature adjacent matrixes, which converts the time-domain features to correlation-based brain network features, thus strengthen the feature representation. Finally, the correlation features of each layer are fused. The fused features are then fed into the channel attention module to filter the channels and classify them using a fully connected network. Finally, we recruit subjects to experience 6 different modes of virtual roller coaster scenes, and collect resting EEG data before and after the task to verify the model. RESULTS: The results show that the accuracy, precision, recall and F1-score of this model for the recognition of VRMS are 98.66 %, 98.65 %, 98.68 %, and 98.66 %, respectively. The proposed model outperforms the current classic and advanced EEG recognition models. SIGNIFICANCE: It shows that this model can be used for the recognition of VRMS based on the resting state EEG.

A stochastic world model on gravity for stability inference.

The fact that objects without proper support will fall to the ground is not only a natural phenomenon, but also common sense in mind. Previous studies suggest that humans may infer objects' stability through a world model that performs mental simulations with a priori knowledge of gravity acting upon the objects. Here we measured participants' sensitivity to gravity to investigate how the world model works. We found that the world model on gravity was not a faithful replica of the physical laws, but instead encoded gravity's vertical direction as a Gaussian distribution. The world model with this stochastic feature fit nicely with participants' subjective sense of objects' stability and explained the illusion that taller objects are perceived as more likely to fall. Furthermore, a computational model with reinforcement learning revealed that the stochastic characteristic likely originated from experience-dependent comparisons between predictions formed by internal simulations and the realities observed in the external world, which illustrated the ecological advantage of stochastic representation in balancing accuracy and speed for efficient stability inference. The stochastic world model on gravity provides an example of how a priori knowledge of the physical world is implemented in mind that helps humans operate flexibly in open-ended environments.

FGF13 enhances the function of TRPV1 by stabilizing microtubules and regulates acute and chronic itch.

Itching is an aversive somatosensation that triggers the desire to scratch. Transient receptor potential (TRP) channel proteins are key players in acute and chronic itch. However, whether the modulatory effect of fibroblast growth factor 13 (FGF13) on acute and chronic itch is associated with TRP channel proteins is unclear. Here, we demonstrated that conditional knockout of Fgf13 in dorsal root ganglion neurons induced significant impairment in scratching behaviors in response to acute histamine-dependent and chronic dry skin itch models. Furthermore, FGF13 selectively regulated the function of the TRPV1, but not the TRPA1 channel on Ca2+ imaging and electrophysiological recordings, as demonstrated by a significant reduction in neuronal excitability and current density induced by TRPV1 channel activation, whereas TRPA1 channel activation had no effect. Changes in channel currents were also verified in HEK cell lines. Subsequently, we observed that selective modulation of TRPV1 by FGF13 required its microtubule-stabilizing effect. Furthermore, in FGF13 knockout mice, only the overexpression of FGF13 with a tubulin-binding domain could rescue TRP channel function and the impaired itch behavior. Our findings reveal a novel mechanism by which FGF13 is involved in TRPV1-dependent itch transduction and provide valuable clues for alleviating pathological itch syndrome.

Per- and polyfluoroalkyl substances and human health outcomes: An umbrella review of systematic reviews with meta-analyses of observational studies.

BACKGROUND: Although evidence on the association between per- and polyfluoroalkyl substances (PFASs) and human health outcomes has grown exponentially, specific health outcomes and their potential associations with PFASs have not been conclusively evaluated. METHODS: We conducted a comprehensive search through the databases of PubMed, Embase, and Web of Science from inception to February 29, 2024, to identify systematic reviews with meta-analyses of observational studies examining the associations between the PFASs and multiple health outcomes. The quality of included studies was evaluated using the A Measurement Tool to Assess Systematic Reviews (AMSTAR) tool, and credibility of evidence was assessed using the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) criteria. The protocol of this umbrella review (UR) had been registered in PROSPERO (CRD 42023480817). RESULTS: The UR identified 157 meta-analyses from 29 articles. Using the AMSTAR measurement tool, all articles were categorized as of moderate-to-high quality. Based on the GRADE assessment, significant associations between specific types of PFASs and low birth weight, tetanus vaccine response, and triglyceride levels showed high certainty of evidence. Moreover, moderate certainty of evidence with statistical significance was observed between PFASs and health outcomes including lower BMI z-score in infancy, poor sperm progressive motility, and decreased risk of preterm birth as well as preeclampsia. Fifty-two (33%) associations (e.g., PFASs and gestational hypertension, cardiovascular disease, etc) presented low certainty evidence. Additionally, eighty-five (55%) associations (e.g., PFASs with infertility, lipid metabolism, etc) presented very low certainty evidence. CONCLUSION: High certainty of evidence supported that certain PFASs were associated with the incidence of low birth weight, low efficiency of the tetanus vaccine, and low triglyceride levels.

Accessing the relationship between six surrogate insulin resistance indexes and the incidence of rapid kidney function decline and the progression to chronic kidney disease among middle-aged and older adults in China: Results from the China health and retirement longitudinal study.

AIMS: Insulin resistance is closely related to kidney function decline, but which insulin resistance index could better predict rapid kidney function decline (RKFD) remains unclear. We aimed to evaluate the prospective association between six insulin resistance indexes: Chinese Visceral Adiposity Index (CVAI), Lipid Accumulation Product (LAP), Atherogenic Index of Plasma (AIP), triglyceride-glucose (TyG) index, triglyceride-glucose × Body Mass Index (TyGBMI) and triglyceride-glucose × waist circumference (TyGWC) with RKFD and further the progression to chronic kidney disease (CKD). METHODS AND MEASUREMENTS: Data were obtained from the China Health and Retirement Longitudinal Study. Participants with normal kidney function (eGFRcr-cys ≥60 ml/min per 1.73 m2) and ≥45 years old were included at the baseline (year 2011). The eGFR was estimated by a combination of serum creatinine and cystatin C. The primary outcome was RKFD, defined as an annualized decline in eGFRcr-cys of 5 ml/min per 1.73 m2 or more. Secondary outcome was progression to CKD under the condition of RKFD, defined as an annualized decline in eGFRcr-cys of 5 ml/min per 1.73 m2 or more combined with eGFRcr-cys <60 ml/min per 1.73 m2 at the exit visit. Logistic analysis was applied for analysis of the association between six insulin resistance indexes and RKFD or progression to CKD. We use receiver operating characteristic curves to study the predictive performance of six insulin resistance indexes. Subgroup analysis were conducted by diabetes or hypertension status of the participants. RESULTS: A total of 3899 participants with normal kidney function were included in this study. After a 3.99 years follow-up, 191 of them ended up with RKFD. Among them, 66 participants progressed to CKD. Logistic analysis showed that per SD increase of all the six insulin resistance indexes were significantly associated with the incidence of RKFD (all P < 0.01), among which, TyGWC had the best predictive value for RKFD. There were significant association between per SD increase of CVAI, LAP, TyGBMI and TyGWC with progression to CKD (all P < 0.01), and CVAI had better predictive role than other indexes. In subgroup analysis, we found that the association between insulin resistance indexes and progression to CKD was more significant in subjects with hypertension or without diabetes. However, no significant differences were observed in the RKFD group. CONCLUSIONS: In this study we proved six insulin resistance indexes were predictively associated with RKFD in Chinese with normal renal function over age 45. TyGWC is the best insulin resistance index for predicting RKFD. CVAI is the best index for predicting further progression to CKD.

Trajectories of Perceived Parental Psychological Control and the Longitudinal Associations with Chinese Adolescents' School Adjustment across High School Years.

Past research supports the detrimental effects of parental psychological control on adolescent school adjustment in both emotional and academic domains. However, how psychological control changes during adolescence, and how such developmental course is related to adolescent psychological well-being and academic functioning are unclear. The direction of effects between parenting and child behaviors is also inconclusive. This 3-year longitudinal study addressed these research gaps by using five waves of survey data on 710 Chinese adolescents of high school ages (Mean age at T1 = 15.54 years, SD = 0.45, 50% males). Using latent growth curve models and latent class growth analysis, the majority of adolescents (about 63%) reported gradual increases of parental psychological control in the first 2 years of high school but a slight decline afterwards, while the other 37% perceived low and stable levels. Results from parallel latent growth modeling suggested that trajectories of psychological control were positively related to developmental trends of internalizing problems (i.e., depression and anxiety) and maladaptive academic functioning, but negatively associated with the trajectory of adaptive academic functioning, as indexed by intercept-intercept and slope-slope associations. The random-intercept cross-lagged models further revealed that psychological control was predictive of adolescent anxiety and lower adaptive academic functioning, and bidirectionally associated with maladaptive academic-related beliefs and behaviors at the within-person level. Taken together, these findings highlight the crucial role of parental psychological control on adolescent school adjustment in the Chinese cultural context and support the reciprocal model of parent-child interactions.

Cerebral autoregulation: A reliable predictor of prognosis in patients receiving intravenous thrombolysis.

AIMS: To investigate the characteristics of dynamic cerebral autoregulation (dCA) after intravenous thrombolysis (IVT) and assess the relationship between dCA and prognosis. METHODS: Patients with unilateral acute ischemic stroke receiving IVT were prospectively enrolled; those who did not were selected as controls. All patients underwent dCA measurements, by quantifying the phase difference (PD) and gain, at 1-3 and 7-10 days after stroke onset. Simultaneously, two dCA-based nomogram models were established to verify the predictive value of dCA for patients with mild-to-moderate stroke. RESULTS: Finally, 202 patients who received IVT and 238 who did not were included. IVT was positively correlated with higher PD on days 1-3 and 7-10 after stroke onset. PD values in both sides at 1-3 days after stroke onset and in the affected side at 7-10 days after onset were independent predictors of unfavorable outcomes in patients who received IVT. Additionally, in patients with mild-to-moderate stroke who received IVT, the dCA-based nomogram models significantly improved the risk predictive ability for 3-month unfavorable outcomes. CONCLUSION: IVT has a positive effect on dCA in patients with acute stroke; furthermore, dCA may be useful to predict the prognosis of patients with IVT.

NLRP4E regulates actin cap formation through SRC and CDC42 during oocyte meiosis.

BACKGROUND: Members of the nucleotide-binding oligomerization domain, leucine rich repeat and pyrin domain containing (NLRP) family regulate various physiological and pathological processes. However, none have been shown to regulate actin cap formation or spindle translocation during the asymmetric division of oocyte meiosis I. NLRP4E has been reported as a candidate protein in female fertility, but its function is unknown. METHODS: Immunofluorescence, reverse transcription polymerase chain reaction (RT-PCR), and western blotting were employed to examine the localization and expression levels of NLRP4E and related proteins in mouse oocytes. small interfering RNA (siRNA) and antibody transfection were used to knock down NLRP4E and other proteins. Immunoprecipitation (IP)-mass spectrometry was used to identify the potential proteins interacting with NLRP4E. Coimmunoprecipitation (Co-IP) was used to verify the protein interactions. Wild type (WT) or mutant NLRP4E messenger RNA (mRNA) was injected into oocytes for rescue experiments. In vitro phosphorylation was employed to examine the activation of steroid receptor coactivator (SRC) by NLRP4E. RESULTS: NLRP4E was more predominant within oocytes compared with other NLRP4 members. NLRP4E knockdown significantly inhibited actin cap formation and spindle translocation toward the cap region, resulting in the failure of polar body extrusion at the end of meiosis I. Mechanistically, GRIN1, and GANO1 activated NLRP4E by phosphorylation at Ser429 and Thr430; p-NLRP4E is translocated and is accumulated in the actin cap region during spindle translocation. Next, we found that p-NLRP4E directly phosphorylated SRC at Tyr418, while p-SRC negatively regulated p-CDC42-S71, an inactive form of CDC42 that promotes actin cap formation and spindle translocation in the GTP-bound form. CONCLUSIONS: NLRP4E activated by GRIN1 and GANO1 regulates actin cap formation and spindle translocation toward the cap region through upregulation of p-SRC-Tyr418 and downregulation of p-CDC42-S71 during meiosis I.

Single-Atom Iron Doped Carbon Dots with Highly Efficient Electrochemiluminescence for Ultrasensitive Detection of MicroRNAs.

Herein, single-atom iron doped carbon dots (SA Fe-CDs) were successfully prepared as novel electrochemiluminescence (ECL) emitters with high ECL efficiency, and a biosensor was constructed to ultrasensitively detect microRNA-222 (miRNA-222). Importantly, compared with the conventional without single-atom doped CDs with low ECL efficiency, SA Fe-CDs exhibited strong ECL efficiency, in which single-atom iron as an advanced coreactant accelerator could significantly enhance the generation of reactive oxygen species (ROS) from the coreactant S2O82- for improving the ECL efficiency. Moreover, a neoteric amplification strategy combining the improved strand displacement amplification with Nt.BbvCI enzyme-induced target amplification (ISDA-EITA) could produce 4 output DNAs in every cycle, which greatly improved the amplification efficiency. Thus, a useful ECL biosensor was built with a detection limit of 16.60 aM in the range of 100 aM to 1 nM for detecting traces of miRNA-222. In addition, miRNA-222 in cancer cell lysate (MHCC-97L) was successfully detected by using the ECL biosensor. Therefore, this strategy provides highly efficient single-atom doped ECL emitters for the construction of sensitive ECL biosensing platforms in the biological field and clinical diagnosis.

Analysis of 15 bile acids in human plasma based on C18 functionalized magnetic organic polymer nanocomposite coupled with liquid chromatography-tandem mass spectrometry.

Because of the "enterohepatic circulation" of bile acid, liver damage can be reflected by monitoring the content of bile acid in the serum of the organism. To monitor the concentration of 15 bile acids in plasma samples, a new technique of PRiME (process, ruggedness, improvement, matrix effect, ease of use) pass-through cleanup procedure combined with high performance liquid chromatography-tandem quadrupole mass spectrometry (HPLC-MS/MS) was developed. The sorbent used in the PRiME pass-through cleanup procedure is a new type of magnetic organic resin composite nano-material modified by C18 (C18-PS-DVB-GMA-Fe3O4), which has high cleanup efficiency of plasma samples. It also shows good performance in the separation and analysis of 15 kinds of bile acids. Under the optimal conditions, the results show higher cleanup efficiency of C18-PS-DVB-GMA-Fe3O4 with recoveries in the range of 82.1-115 %. The limit of quantitative (LOQs) of 15 bile acids were in the range of 0.033 µg/L-0.19 µg/L, and the RSD values of 15 bile acids were in the range of 3.00-11.9 %. Validation results on linearity, specificity, accuracy and precision, as well as on the application to analysis of 15 bile acids in 100 human plasma samples demonstrate the applicability to clinical studies.

Compound heterozygous ABCA12 variants identified in a Chinese patient with congenital ichthyosiform erythroderma: Advancing genotype-phenotype correlations and literature review.

BACKGROUND: Ichthyosis is a common keratotic skin disease with high clinical, etiological and genetic heterogeneity. There are four types of non-syndromic hereditary ichthyoses, among which autosomal recessive congenital ichthyosis (ARCI) is a heterogeneous group of recessive Mendelian disorders. ARCI present with different phenotypes and ABCA12 pathogenic variants have been shown to cause complex ARCI phenotypes, including harlequin ichthyosis (HI), lamellar ichthyosis (LI) and congenital ichthyosiform erythroderma (CIE). METHODS: A sporadic male patient, clinically diagnosed with CIE, was enrolled in this study. Exome sequencing was combined with Sanger sequencing to confirm the diagnosis and identify the pathogenic variants. In silico predictions were made using multiple software programs, and the identified variants were interpreted using the ACMG guidelines. A review of all literature reported ABCA12 variants was performed to explore genotype-phenotype correlations. RESULTS: Compound heterozygous ABCA12 variants [c.5381+1G>A and c.5485G>C (p.Asp1829His)] (NM_173076) were identified. The two variants were not detected in the public database. c.5381+1G>A is predicted to affect ABCA12 mRNA splicing and Asp1829 is highly conserved among various species. In silico analysis suggested that these two variants were responsible for the phenotype of the patient. Genotype-phenotype correlation analysis showed that biallelic truncation variants and/or exon/amino acid deletions in ABCA12 are the most common causes of HI. Biallelic missense variants are most common in LI and CIE. CONCLUSIONS: The compound heterozygous ABCA12 variants caused the CIE phenotype observed in the patient. The spectrum of ABCA12 pathogenic variants were broaden. Genotype-phenotype correlation analysis provided detailed evidence which can be used in future prenatal diagnosis and can inform the need for genetic counselling for patients with ABCA12-related ARCIs.

Predicting rectal cancer prognosis from histopathological images and clinical information using multi-modal deep learning.

Objective: The objective of this study was to provide a multi-modal deep learning framework for forecasting the survival of rectal cancer patients by utilizing both digital pathological images data and non-imaging clinical data. Materials and methods: The research included patients diagnosed with rectal cancer by pathological confirmation from January 2015 to December 2016. Patients were allocated to training and testing sets in a randomized manner, with a ratio of 4:1. The tissue microarrays (TMAs) and clinical indicators were obtained. Subsequently, we selected distinct deep learning models to individually forecast patient survival. We conducted a scanning procedure on the TMAs in order to transform them into digital pathology pictures. Additionally, we performed pre-processing on the clinical data of the patients. Subsequently, we selected distinct deep learning algorithms to conduct survival prediction analysis using patients' pathological images and clinical data, respectively. Results: A total of 292 patients with rectal cancer were randomly allocated into two groups: a training set consisting of 234 cases, and a testing set consisting of 58 instances. Initially, we make direct predictions about the survival status by using pre-processed Hematoxylin and Eosin (H&E) pathological images of rectal cancer. We utilized the ResNest model to extract data from histopathological images of patients, resulting in a survival status prediction with an AUC (Area Under the Curve) of 0.797. Furthermore, we employ a multi-head attention fusion (MHAF) model to combine image features and clinical features in order to accurately forecast the survival rate of rectal cancer patients. The findings of our experiment show that the multi-modal structure works better than directly predicting from histopathological images. It achieves an AUC of 0.837 in predicting overall survival (OS). Conclusions: Our study highlights the potential of multi-modal deep learning models in predicting survival status from histopathological images and clinical information, thus offering valuable insights for clinical applications.