A systematic CRISPR screen reveals redundant and specific roles for Dscam1 isoform diversity in neuronal wiring.

Drosophila melanogaster Down syndrome cell adhesion molecule 1 (Dscam1) encodes 19,008 diverse ectodomain isoforms via the alternative splicing of exon 4, 6, and 9 clusters. However, whether individual isoforms or exon clusters have specific significance is unclear. Here, using phenotype-diversity correlation analysis, we reveal the redundant and specific roles of Dscam1 diversity in neuronal wiring. A series of deletion mutations were performed from the endogenous locus harboring exon 4, 6, or 9 clusters, reducing to 396 to 18,612 potential ectodomain isoforms. Of the 3 types of neurons assessed, dendrite self/non-self discrimination required a minimum number of isoforms (approximately 2,000), independent of exon clusters or isoforms. In contrast, normal axon patterning in the mushroom body and mechanosensory neurons requires many more isoforms that tend to associate with specific exon clusters or isoforms. We conclude that the role of the Dscam1 diversity in dendrite self/non-self discrimination is nonspecifically mediated by its isoform diversity. In contrast, a separate role requires variable domain- or isoform-related functions and is essential for other neurodevelopmental contexts, such as axonal growth and branching. Our findings shed new light on a general principle for the role of Dscam1 diversity in neuronal wiring.

Metamorphism-facilitated faulting in deforming orthopyroxene: Implications for global intermediate-depth seismicity.

SignificanceThe exothermic metamorphic reaction in orthopyroxene (Opx), a major component of oceanic lithospheric mantle, is shown to trigger brittle failure in laboratory deformation experiments under conditions where garnet exsolution takes place. The reaction product is an extremely fine-grained material, forming narrow reaction zones that are mechanically weak, thereby facilitating macroscopic faulting. Oceanic subduction zones are characterized by two separate bands of seismicity, known as the double seismic zone. The upper band of seismicity, located in the oceanic crust, is well explained by dehydration-induced mechanical instability. Our newly discovered metamorphism-induced mechanical instability provides an alternative physical mechanism for earthquakes in the lower band of seismicity (located in the oceanic lithospheric mantle), with no requirement of hydration/dehydration processes.

Recent advancements in artificial intelligence for breast cancer: Image augmentation, segmentation, diagnosis, and prognosis approaches.

Breast cancer is a significant global health burden, with increasing morbidity and mortality worldwide. Early screening and accurate diagnosis are crucial for improving prognosis. Radiographic imaging modalities such as digital mammography (DM), digital breast tomosynthesis (DBT), magnetic resonance imaging (MRI), ultrasound (US), and nuclear medicine techniques, are commonly used for breast cancer assessment. And histopathology (HP) serves as the gold standard for confirming malignancy. Artificial intelligence (AI) technologies show great potential for quantitative representation of medical images to effectively assist in segmentation, diagnosis, and prognosis of breast cancer. In this review, we overview the recent advancements of AI technologies for breast cancer, including 1) improving image quality by data augmentation, 2) fast detection and segmentation of breast lesions and diagnosis of malignancy, 3) biological characterization of the cancer such as staging and subtyping by AI-based classification technologies, 4) prediction of clinical outcomes such as metastasis, treatment response, and survival by integrating multi-omics data. Then, we then summarize large-scale databases available to help train robust, generalizable, and reproducible deep learning models. Furthermore, we conclude the challenges faced by AI in real-world applications, including data curating, model interpretability, and practice regulations. Besides, we expect that clinical implementation of AI will provide important guidance for the patient-tailored management.

In Situ Electrospinning MOF-Derived Highly Dispersed α-Cobalt Confined in Nitrogen-Doped Carbon Nanofibers Nanozyme for Biomolecule Monitoring.

Designing a metal-organic framework (MOF)-derived nanozyme with highly dispersed active sites and high catalytic activity as well as robust structure for colorimetric biosensing of diverse biomolecules remains a substantial challenge. Here, an MOF-derived highly dispersed and pure α-cobalt confined in a nitrogen-doped carbon nanofiber (α-Co@NCNF) nanozyme with superior glucose oxidase (GOD)- and peroxidase (POD)-like activities was constructed for colorimetric assay of multiple biomolecules. Specifically, the α-Co@NCNF nanozyme was synthesized, utilizing in situ electrospinning Co-MOFs into polyacrylonitrile nanofiber (PAN) followed by a pyrolysis process. Taking advantage of the in situ electrospinning strategy, the α-Co nanoparticles were confined in continuous porous NCNF to restrict the growth and prevent the aggregation and oxidation during the pyrolysis process. The resulting special structure considerably improved the enzyme-like performance. A series of experiments validate that the enzyme-like activity of the α-Co@NCNF nanozyme was superior to that of Co@CoO@NCNF (derivatives from Co-MOFs grown on the surface of PAN nanofiber) and nature enzymes. Furthermore, α-Co@NCNF nanozyme-based colorimetric biosensing was developed for monitoring glucose, hydrogen peroxide (H2O2), and glutathione (GSH) and the corresponding linear ranges are 0.1-50 and 50-900 µM and 5-55 and 0.1-20 µM accompanied by the corresponding low detection of 0.03, 1.66, and 0.03 µM. The proposed method for the construction of α-Co@NCNF nanozyme with dual enzyme-like properties provides a new insight for designing novel nanozymes and has prospects for application in colorimetric biosensing.

Overexpression of rice OsNRT1.1A/OsNPF6.3 enhanced the nitrogen use efficiency of wheat under low nitrogen conditions.

MAIN CONCLUSION: Overexpression of OsNRT1.1A promotes early heading and increases the tolerance in wheat under nitrogen deficiency conditions. The application of inorganic nitrogen (N) fertilizers is a major driving force for crop yield improvement. However, the overuse of fertilizers significantly raises production costs and leads to environmental problems, making it critical to enhance crop nitrogen use efficiency (NUE) for the sake of sustainable agriculture. In this study, we created a series of transgenic wheat lines carrying the rice OsNRT1.1A gene, which encodes a nitrate transporter, to investigate its possible application in improving NUE in wheat. The transgenic wheat exhibited traits such as early maturation that were highly consistent with the overexpression of OsNRT1.1A in Arabidopsis and rice. However, we also observed that overexpression of the OsNRT1.1A gene in wheat can facilitate the growth of roots under low N conditions but has no effect on other aspects of growth and development under normal N conditions. Thus, it may lead to the improvement of wheat low N tolerance,which is different from the effects reported in other plants. A field trial analysis showed that transgenic wheat exhibited increased grain yield per plant under low N conditions. Moreover, transcriptome analysis indicated that OsNRT1.1A increased the expression levels of N uptake and utilization genes in wheat, thereby promoting plant growth under low N conditions. Taken together, our results indicated that OsNRT1.1A plays an important role in improving NUE in wheat with low N availability.

Epstein-Barr virus-driven metabolic alterations contribute to the viral lytic reactivation and tumor progression in nasopharyngeal carcinoma.

Metabolic reprogramming induced by Epstein-Barr virus (EBV) often mirrors metabolic changes observed in cancer cells. Accumulating evidence suggests that lytic reactivation is crucial in EBV-associated oncogenesis. The aim of this study was to explore the role of metabolite changes in EBV-associated malignancies and viral life cycle control. We first revealed that EBV (LMP1) accelerates the secretion of the oncometabolite D-2HG, and serum D-2HG level is a potential diagnostic biomarker for NPC. EBV (LMP1)-driven metabolite changes disrupts the homeostasis of global DNA methylation and demethylation, which have a significantly inhibitory effect on active DNA demethylation and 5hmC content. We found that loss of 5hmC indicates a poor prognosis for NPC patients, and that 5hmC modification is a restriction factor of EBV reactivation. We confirmed a novel EBV reactivation inhibitor, α-KG, which inhibits the expression of EBV lytic genes with CpG-containing ZREs and the latent-lytic switch by enhancing 5hmC modification. Our results demonstrate a novel mechanism of which metabolite abnormality driven by EBV controls the viral lytic reactivation through epigenetic modification. This study presents a potential strategy for blocking EBV reactivation, and provides potential targets for the diagnosis and therapy of NPC.

Parallel CNN-Deep Learning Clinical-Imaging Signature for Assessing Pathologic Grade and Prognosis of Soft Tissue Sarcoma Patients.

BACKGROUND: Traditional biopsies pose risks and may not accurately reflect soft tissue sarcoma (STS) heterogeneity. MRI provides a noninvasive, comprehensive alternative. PURPOSE: To assess the diagnostic accuracy of histological grading and prognosis in STS patients when integrating clinical-imaging parameters with deep learning (DL) features from preoperative MR images. STUDY TYPE: Retrospective/prospective. POPULATION: 354 pathologically confirmed STS patients (226 low-grade, 128 high-grade) from three hospitals and the Cancer Imaging Archive (TCIA), divided into training (n = 185), external test (n = 125), and TCIA cohorts (n = 44). 12 patients (6 low-grade, 6 high-grade) were enrolled into prospective validation cohort. FIELD STRENGTH/SEQUENCE: 1.5 T and 3.0 T/Unenhanced T1-weighted and fat-suppressed-T2-weighted. ASSESSMENT: DL features were extracted from MR images using a parallel ResNet-18 model to construct DL signature. Clinical-imaging characteristics included age, gender, tumor-node-metastasis stage and MRI semantic features (depth, number, heterogeneity at T1WI/FS-T2WI, necrosis, and peritumoral edema). Logistic regression analysis identified significant risk factors for the clinical model. A DL clinical-imaging signature (DLCS) was constructed by incorporating DL signature with risk factors, evaluated for risk stratification, and assessed for progression-free survival (PFS) in retrospective cohorts, with an average follow-up of 23 ± 22 months. STATISTICAL TESTS: Logistic regression, Cox regression, Kaplan-Meier curves, log-rank test, area under the receiver operating characteristic curve (AUC)，and decision curve analysis. A P-value <0.05 was considered significant. RESULTS: The AUC values for DLCS in the external test, TCIA, and prospective test cohorts (0.834, 0.838, 0.819) were superior to clinical model (0.662, 0.685, 0.694). Decision curve analysis showed that the DLCS model provided greater clinical net benefit over the DL and clinical models. Also, the DLCS model was able to risk-stratify patients and assess PFS. DATA CONCLUSION: The DLCS exhibited strong capabilities in histological grading and prognosis assessment for STS patients, and may have potential to aid in the formulation of personalized treatment plans. TECHNICAL EFFICACY: Stage 2.

Deep learning for malignancy risk estimation of incidental sub-centimeter pulmonary nodules on CT images.

OBJECTIVES: To establish deep learning models for malignancy risk estimation of sub-centimeter pulmonary nodules incidentally detected by chest CT and managed in clinical settings. MATERIALS AND METHODS: Four deep learning models were trained using CT images of sub-centimeter pulmonary nodules from West China Hospital, internally tested, and externally validated on three cohorts. The four models respectively learned 3D deep features from the baseline whole lung region, baseline image patch where the nodule located, baseline nodule box, and baseline plus follow-up nodule boxes. All regions of interest were automatically segmented except that the nodule boxes were additionally manually checked. The performance of models was compared with each other and that of three respiratory clinicians. RESULTS: There were 1822 nodules (981 malignant) in the training set, 806 (416 malignant) in the testing set, and 357 (253 malignant) totally in the external sets. The area under the curve (AUC) in the testing set was 0.754, 0.855, 0.928, and 0.942, respectively, for models derived from baseline whole lung, image patch, nodule box, and the baseline plus follow-up nodule boxes. When baseline models externally validated (follow-up images not available), the nodule-box model outperformed the other two with AUC being 0.808, 0.848, and 0.939 respectively in the three external datasets. The resident, junior, and senior clinicians achieved an accuracy of 67.0%, 82.5%, and 90.0%, respectively, in the testing set. The follow-up model performed comparably to the senior clinician. CONCLUSION: The deep learning algorithms solely mining nodule information can efficiently predict malignancy of incidental sub-centimeter pulmonary nodules. CLINICAL RELEVANCE STATEMENT: The established models may be valuable for supporting clinicians in routine clinical practice, potentially reducing the number of unnecessary examinations and also delays in diagnosis. KEY POINTS: • According to different regions of interest, four deep learning models were developed and compared to evaluate the malignancy of sub-centimeter pulmonary nodules by CT images. • The models derived from baseline nodule box or baseline plus follow-up nodule boxes demonstrated sufficient diagnostic accuracy (86.4% and 90.4% in the testing set), outperforming the respiratory resident (67.0%) and junior clinician (82.5%). • The proposed deep learning methods may aid clinicians in optimizing follow-up recommendations for sub-centimeter pulmonary nodules and may lead to fewer unnecessary diagnostic interventions.

Carbon dots@noble metal nanoparticle composites: research progress report.

Carbon dots@noble metal nanoparticle composites are formed by combining carbon dots and metal nanoparticles using various strategies. Carbon dots exhibit a reducing ability and function as stabilisers; consequently, metal-ion solutions can be directly reduced by them to synthesise gold, silver, and gold-silver alloy particles. Carbon dots@gold/silver/gold-silver particle composites have demonstrated the potential for several practical applications owing to their superior properties and simple preparation process. Until now, several review articles have been published to summarise fluorescent carbon dots or noble metal nanomaterials. Compared with metal-free carbon dots, carbon dots@noble metal nanoparticles have a unique morphology and structure, resulting in new physicochemical properties, which allow for sensing, bioimaging, and bacteriostasis applications. Therefore, to promote the effective development of carbon dots@noble metal nanoparticle composites, this paper primarily reviews carbon dots@gold/silver/gold-silver alloy nanoparticle composites for the first time in terms of the following aspects. (1) The synthesis strategies of carbon dots@noble metal nanoparticle composites are outlined. The principle and function of carbon dots in the synthesis strategies are examined. The advantages and disadvantages of these methods and composites are analysed. (2) The characteristics and properties of such composites are described. (3) The applications of these composite materials are summarised. Finally, the potentials and limitations of carbon dots@noble metal nanoparticle composites are discussed, thus laying the foundation for their further development.

Rhizophagus irregularis and biochar can synergistically improve the physiological characteristics of saline-alkali resistance of switchgrass.

Inoculation of arbuscular mycorrhizal fungi (AMF) or biochar (BC) application can improve photosynthesis and promote plant growth under saline-alkali stress. However, little is known about the effects of the two combined on growth and physiological characteristics of switchgrass under saline-alkali stress. This study examined the effects of four treatments: (1) no AMF inoculation and no biochar addition (control), (2) biochar (BC) alone, (3) AMF (Rhizophagus irregularis, Ri) alone, and (4) the combination of both (BC+Ri) on the plant biomass, antioxidant enzymes, chlorophyll, and photosynthetic parameters of switchgrass under saline-alkali stress. The results showed that the above-ground, belowground and total biomass of switchgrass in the BC+Ri treatment group was significantly higher (+136.7%, 120.2% and 132.4%, respectively) than in other treatments compared with Control. BC+Ri treatment significantly increased plant leaves' relative chlorophyll content, antioxidant enzyme activity, and photosynthesis parameters. It is worth noting that the transpiration rate, stomatal conductance, net photosynthetic rate, PSII efficiency and other photosynthetic-related indexes of the BC+Ri treatment group were the highest (38% to 54% higher than other treatments). The fitting results of light response and CO2 response curves showed that the light saturation point, light compensation point, maximum carboxylation rate and maximum electron transfer rate of switchgrass in the Ri+BC treatment group were the highest. In conclusion, biochar combined with Ri has potential beneficial effects on promoting switchgrass growth under saline-alkali stress and improving the activity of antioxidant enzymes and photosynthetic characteristics of plants.

Rapid and sensitive visual detection of avian leukosis virus by reverse transcription loop-mediated isothermal amplification combined with a lateral flow immunochromatographic strip assay.

Considering that avian leukosis virus (ALV) infection has inflicted massive economic losses on the poultry breeding industry in most countries, its early diagnosis remains an important measure for timely treatment and control of the disease, for which a rapid and sensitive point-of-care test is required. We established a user-friendly, economical, and rapid visualization method for ALV amplification products based on reverse transcription loop-mediated isothermal amplification (RT-LAMP) combined with an immunochromatographic strip in a lateral flow device (LFD). Using the ALVp27 gene as the target, five RT-LAMP primers and one fluorescein-isothiocyanate-labeled probe were designed. After 60 min of RT-LAMP amplification at 64 °C, the products could be visualized directly using the LFD. The detection limit of this assay for ALV detection was 102 RNA copies/µL, and the sensitivity was 100 times that of reverse transcription polymerase chain reaction (RT-PCR), showing high specificity and sensitivity. To verify the clinical practicality of this assay for detecting ALV, the gold standard RT-PCR method was used for comparison, and consistent results were obtained with both assays. Thus, the assay described here can be used for rapid detection of ALV in resource-limited environments.

Myeloid-derived growth factor suppresses VSMC dedifferentiation and attenuates postinjury neointimal formation in rats by activating S1PR2 and its downstream signaling.

Restenosis after angioplasty is caused usually by neointima formation characterized by aberrant vascular smooth muscle cell (VSMC) dedifferentiation. Myeloid-derived growth factor (MYDGF), secreted from bone marrow-derived monocytes and macrophages, has been found to have cardioprotective effects. In this study we investigated the effect of MYDGF to postinjury neointimal formation and the underlying mechanisms. Rat carotid arteries balloon-injured model was established. We found that plasma MYDGF content and the level of MYDGF in injured arteries were significantly decreased after balloon injury. Local application of exogenous MYDGF (50 µg/mL) around the injured vessel during balloon injury markedly ameliorated the development of neointimal formation evidenced by relieving the narrow endovascular diameter, improving hemodynamics, and reducing collagen deposition. In addition, local application of MYDGF inhibited VSMC dedifferentiation, which was proved by reversing the elevated levels of osteopontin (OPN) protein and decreased levels of α-smooth muscle actin (α-SMA) in the left carotid arteries. We showed that PDGF-BB (30 ng/mL) stimulated VSMC proliferation, migration and dedifferentiation in vitro; pretreatment with MYDGF (50-200 ng/mL) concentration-dependently eliminated PDGF-BB-induced cell proliferation, migration and dedifferentiation. Molecular docking revealed that MYDGF had the potential to bind with sphingosine-1-phosphate receptor 2 (S1PR2), which was confirmed by SPR assay and Co-IP analysis. Pretreatment with CCG-1423 (Rho signaling inhibitor), JTE-013 (S1PR2 antagonist) or Ripasudil (ROCK inhibitor) circumvented the inhibitory effects of MYDGF on VSMC phenotypic switching through inhibiting S1PR2 or its downstream RhoA-actin monomers (G-actin) /actin filaments (F-actin)-MRTF-A signaling. In summary, this study proves that MYDGF relieves neointimal formation of carotid arteries in response to balloon injury in rats, and suppresses VSMC dedifferentiation induced by PDGF-BB via S1PR2-RhoA-G/F-actin-MRTF-A signaling pathway. In addition, our results provide evidence for cross talk between bone marrow and vasculature.

Key technology of vector removal decoupling in a slope-based figuring model and application in continuous phase plate fabrication.

For the high-precision fabrication of a continuous phase plate (CPP), a combined decoupling algorithm of single-step decoupling based on the Clairaut-Schwarz theorem and global decoupling by stagewise iteration is proposed. It attempts to address the problem of the low accuracy and limitation of the existing slope-based figuring (SF) model in two-dimensional applications caused by the vector removal coupling between the tool slope influence function and the material removal slope due to the inherent convolution effect in the SF model. The shortcomings of CPP interferometry and the application bottleneck of the Hartmann test in traditional height-based figuring model are studied. The generation mechanism of vector removal coupling is analyzed and compensated. A CPP of 85m m×85m m was successfully machined by the decoupled slope-based figuring model, and the root mean square (RMS) of the surface height error accounted for 6.01% of the RMS of the design value. The research results can effectively improve the convergence and certainty of CPP fabrication using the slope-based figuring model.

Survival analysis of patients with extrahepatic cholangiocarcinoma: a nomogram for clinical and MRI features.

BACKGROUND: This study aimed to establish a predictive model to estimate the postoperative prognosis of patients with extrahepatic cholangiocarcinoma (ECC) based on preoperative clinical and MRI features. METHODS: A total of 104 patients with ECC confirmed by surgery and pathology were enrolled from January 2013 to July 2021, whose preoperative clinical, laboratory, and MRI data were retrospectively collected and examined, and the effects of clinical and imaging characteristics on overall survival (OS) were analyzed by constructing Cox proportional hazard regression models. A nomogram was constructed to predict OS, and calibration curves and time-dependent receiver operating characteristic (ROC) curves were employed to assess OS accuracy. RESULTS: Multivariate regression analyses revealed that gender, DBIL, ALT, GGT, tumor size, lesion's position, the signal intensity ratio of liver to paraspinal muscle (SIRLiver/Muscle), and the signal intensity ratio of spleen to paraspinal muscle (SIRSpleen/Muscle) on T2WI sequences were significantly associated with OS, and these variables were included in a nomogram. The concordance index of nomogram for predicting OS was 0.766, and the AUC values of the nomogram predicting 1-year and 2-year OS rates were 0.838 and 0.863, respectively. The calibration curve demonstrated good agreement between predicted and observed OS. 5-fold and 10-fold cross-validation show good stability of nomogram predictions. CONCLUSIONS: Our nomogram based on clinical, laboratory, and MRI features well predicted OS of ECC patients, and could be considered as a convenient and personalized prediction tool for clinicians to make decisions.

Concentrations of per- and polyfluoroalkyl substances in vegetables from Sydney and Newcastle, Australia.

BACKGROUND: This study investigated per- and polyfluoroalkyl substances (PFASs) in 53 fruit and vegetable samples collected from a local wholesale and retail market in Sydney and a local supermarket in Newcastle. As there is limited information about PFAS levels in vegetables on the market, this study aimed to fill this gap and assess potential risks for humans through consumption of these vegetables. METHODS: QuEChERS extraction - a solid-phase extraction method, a portmanteau word formed from 'quick, easy, cheap, effective, rugged and safe' - followed by enhanced matrix removal-lipid cleaning and liquid chromatography-tandem mass spectrometry analysis were used to detect 30 PFASs in vegetables. RESULTS: PFOA was detected in 7 out of the 53 samples, with concentrations of 0.038-1.996 ng g-1 fresh weight; PFOS was detected in 2 samples only, with concentrations ranging from 0.132 to 0.911 ng g-1 fresh weight. PFHxS was not detected in any sample in this study. PFOA and PFOS concentrations measured in vegetables in this study constituted daily intake of 2.03 ng kg-1 body weight (BW) and 1.98 ng kg-1 BW, respectively, according to recommended daily vegetable intake and BW data from the Australian Bureau of Statistics. The most sensitive population group is girls of 4-8 years of age. These estimated exposure levels represent up to 1.3% of the tolerable daily intake for PFOA (160 ng kg-1 BW) and 9.9% for PFOS (20 ng kg-1 BW) according to Food Standards Australia New Zealand. Consumption of the vegetables from the study locations poses a marginal risk to human health. © 2024 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Metabolic engineering Corynebacterium glutamicum for D-chiro-inositol production.

D-chiro-inositol (DCI) is a potential drug for the treatment of type II diabetes and polycystic ovary syndrome. In order to effectively synthesize DCI in Corynebacterium glutamicum, the genes related to inositol catabolism in clusters iol1 and iol2 were knocked out in C. glutamicum SN01 to generate the chassis strain DCI-1. DCI-1 did not grow in and catabolize myo-inositol (MI). Subsequently, different exogenous and endogenous inosose isomerases were expressed in DCI-1 and their conversion ability of DCI from MI were compared. After fermentation, the strain DCI-7 co-expressing inosose isomerase IolI2 and inositol dehydrogenase IolG was identified as the optimal strain. Its DCI titer reached 3.21 g/L in the presence of 20 g/L MI. On this basis, the pH, temperature and MI concentration during whole-cell conversion of DCI by strain DCI-7 were optimized. Finally, the optimal condition that achieved the highest DCI titer of 6.96 g/L were obtained at pH 8.0, 37 °C and addition of 40 g/L MI. To our knowledge, it is the highest DCI titer ever reported.

Blast injuries with contrasting outcomes treated by military surgery strategies: A case report.

The treatment strategy for blast injuries is closely linked to the clinical outcome of blast injury casualties. However, the application of military surgery experience to blast injuries caused by production safety accidents is relatively uncommon. In this study, the authors present 2 cases of blast injuries caused by one gas explosion, both cases involved individuals of the same age and gender and experienced similar degree of injury. The authors highlight the importance of using a military surgery treatment strategy, specifically emphasizing the need to understand the concept of damage control and disposal. It is recommended that relevant training in this area should be strengthened to improve the clinical treatment of such injuries. This study provides a valuable reference for healthcare professionals dealing with blast injuries.

Risk factors and predictive model of cerebral edema after road traffic accidents-related traumatic brain injury.

PURPOSE: Cerebral edema (CE) is the main secondary injury following traumatic brain injury (TBI) caused by road traffic accidents (RTAs). It is challenging to be predicted timely. In this study, we aimed to develop a prediction model for CE by identifying its risk factors and comparing the timing of edema occurrence in TBI patients with varying levels of injuries. METHODS: This case-control study included 218 patients with TBI caused by RTAs. The cohort was divided into CE and non-CE groups, according to CT results within 7 days. Demographic data, imaging data, and clinical data were collected and analyzed. Quantitative variables that follow normal distribution were presented as mean ± standard deviation, those that do not follow normal distribution were presented as median (Q1, Q3). Categorical variables were expressed as percentages. The Chi-square test and logistic regression analysis were used to identify risk factors for CE. Logistic curve fitting was performed to predict the time to secondary CE in TBI patients with different levels of injuries. The efficacy of the model was evaluated using the receiver operator characteristic curve. RESULTS: According to the study, almost half (47.3%) of the patients were found to have CE. The risk factors associated with CE were bilateral frontal lobe contusion, unilateral frontal lobe contusion, cerebral contusion, subarachnoid hemorrhage, and abbreviated injury scale (AIS). The odds ratio values for these factors were 7.27 (95% confidence interval (CI): 2.08 - 25.42, p = 0.002), 2.85 (95% CI: 1.11 - 7.31, p = 0.030), 2.62 (95% CI: 1.12 - 6.13, p = 0.027), 2.44 (95% CI: 1.25 - 4.76, p = 0.009), and 1.5 (95% CI: 1.10 - 2.04, p = 0.009), respectively. We also observed that patients with mild/moderate TBI (AIS ≤ 3) had a 50% probability of developing CE 19.7 h after injury (χ2 = 13.82, adjusted R2 = 0.51), while patients with severe TBI (AIS > 3) developed CE after 12.5 h (χ2 = 18.48, adjusted R2 = 0.54). Finally, we conducted a receiver operator characteristic curve analysis of CE time, which showed an area under the curve of 0.744 and 0.672 for severe and mild/moderate TBI, respectively. CONCLUSION: Our study found that the onset of CE in individuals with TBI resulting from RTAs was correlated with the severity of the injury. Specifically, those with more severe injuries experienced an earlier onset of CE. These findings suggest that there is a critical time window for clinical intervention in cases of CE secondary to TBI.

[Exosome and prevention of Alzheimer's disease: based on theory of kidney storing essence].

The theory of kidney storing essence storage, an important part of the basic theory of traditional Chinese medicine(TCM), comes from the Chapter 9 Discussion on Six-Plus-Six System and the Manifestations of the Viscera in the Plain Questions, which says that "the kidney manages closure and is the root of storage and the house of Jing(Essence)". According to this theory, essence is the fundamental substance of human life activities and it is closely related to the growth and development of the human body. Alzheimer's disease(AD) is one of the common neurodegenerative diseases, with the main pathological features of Aß deposition and Tau phosphorylation, which activate neurotoxic reactions and eventually lead to neuronal dysfunction and cell death, severely impairing the patient's cognitive and memory functions. Although research results have been achieved in the TCM treatment of AD, the complex pathogenesis of AD makes it difficult to develop the drugs capable of curing AD. The stem cell therapy is an important method to promote self-repair and regeneration, and bone marrow mesenchymal stem cells(BMSCs) as adult stem cells have the ability of multi-directional differentiation. By reviewing the relevant literature, this paper discusses the association between BMSCs and the TCM theory of kidney storing essence, and expounds the material basis of this theory from the perspective of molecular biology. Studies have shown that TCM with the effect of tonifying the kidney in the treatment of AD are associated with BMSCs. Exosomes produced by such cells are one of the main substances affecting AD. Exosomes containing nucleic acids, proteins, and lipids can participate in intercellular communication, regulate cell function, and affect AD by reducing Aß deposition, inhibiting Tau protein phosphorylation and neuroinflammation, and promoting neuronal regeneration. Therefore, discussing the prevention and treatment of exosomes and AD based on the theory of kidney storing essence will provide a new research idea for the TCM treatment of AD.

Catalytic Asymmetric Synthesis of Atropisomers Bearing Multiple Chiral Elements: An Emerging Field.

With the rapid development of asymmetric catalysis, the demand for the enantioselective synthesis of complex and diverse molecules with different chiral elements is increasing. Owing to the unique features of atropisomerism, the catalytic asymmetric synthesis of atropisomers has attracted a considerable interest from the chemical science community. In particular, introducing additional chiral elements, such as carbon centered chirality, heteroatomic chirality, planar chirality, and helical chirality, into atropisomers provides an opportunity to incorporate new properties into axially chiral compounds, thus expanding the potential applications of atropisomers. Thus, it is important to perform catalytic asymmetric transformations to synthesize atropisomers bearing multiple chiral elements. In spite of challenges in such transformations, in recent years, chemists have devised powerful strategies under asymmetric organocatalysis or metal catalysis, synthesizing a wide range of enantioenriched atropisomers bearing multiple chiral elements. Therefore, the catalytic asymmetric synthesis of atropisomers bearing multiple chiral elements has become an emerging field. This review summarizes the rapid progress in this field and indicates challenges, thereby promoting this field to a new horizon.