Endotype-driven Co-module mechanisms of danhong injection in the Co-treatment of cardiovascular and cerebrovascular diseases: A modular-based drug and disease integrated analysis.

ETHNOPHARMACOLOGICAL RELEVANCE: Cardiovascular and cerebrovascular diseases are the leading causes of death worldwide and interact closely with each other. Danhong Injection (DHI) is a widely used preparation for the co-treatment of brain and heart diseases (CTBH). However, the underlying molecular endotype mechanisms of DHI in the CTBH remain unclear. AIM OF THIS STUDY: To elucidate the underlying endotype mechanisms of DHI in the CTBH. MATERIALS AND METHODS: In this study, we proposed a modular-based disease and drug-integrated analysis (MDDIA) strategy for elucidating the systematic CTBH mechanisms of DHI using high-throughput transcriptome-wide sequencing datasets of DHI in the treatment of patients with stable angina pectoris (SAP) and cerebral infarction (CI). First, we identified drug-targeted modules of DHI and disease modules of SAP and CI based on the gene co-expression networks of DHI therapy and the protein-protein interaction networks of diseases. Moreover, module proximity-based topological analyses were applied to screen CTBH co-module pairs and driver genes of DHI. At the same time, the representative driver genes were validated via in vitro experiments on hypoxia/reoxygenation-related cardiomyocytes and neuronal cell lines of H9C2 and HT22. RESULTS: Seven drug-targeted modules of DHI and three disease modules of SAP and CI were identified by co-expression networks. Five modes of modular relationships between the drug and disease modules were distinguished by module proximity-based topological analyses. Moreover, 13 targeted module pairs and 17 driver genes associated with DHI in the CTBH were also screened. Finally, the representative driver genes AKT1, EDN1, and RHO were validated by in vitro experiments. CONCLUSIONS: This study, based on clinical sequencing data and modular topological analyses, integrated diseases and drug targets. The CTBH mechanism of DHI may involve the altered expression of certain driver genes (SRC, STAT3, EDN1, CYP1A1, RHO, RELA) through various enriched pathways, including the Wnt signaling pathway.

The tetraploid wheat (Triticum dicoccum (Schrank) Schuebl.) improves nitrogen uptake and assimilation adaptation to nitrogen-deficit stress.

MAIN CONCLUSION: The genetic diversity in tetraploid wheat provides a genetic pool for improving wheat productivity and environmental resilience. The tetraploid wheat had strong N uptake, translocation, and assimilation capacity under N deficit stress, thus alleviating growth inhibition and plant N loss to maintain healthy development and adapt to environments with low N inputs. Tetraploid wheat with a rich genetic variability provides an indispensable genetic pool for improving wheat yield. Mining the physiological mechanisms of tetraploid wheat in response to nitrogen (N) deficit stress is important for low-N-tolerant wheat breeding. In this study, we selected emmer wheat (Kronos, tetraploid), Yangmai 25 (YM25, hexaploid), and Chinese spring (CS, hexaploid) as materials. We investigated the differences in the response of root morphology, leaf and root N accumulation, N uptake, translocation, and assimilation-related enzymes and gene expression in wheat seedlings of different ploidy under N deficit stress through hydroponic experiments. The tetraploid wheat (Kronos) had stronger adaptability to N deficit stress than the hexaploid wheats (YM25, CS). Kronos had better root growth under low N stress, expanding the N uptake area and enhancing N uptake to maintain higher NO3- and soluble protein contents. Kronos exhibited high TaNRT1.1, TaNRT2.1, and TaNRT2.2 expression in roots, which promoted NO3- uptake, and high TaNRT1.5 and TaNRT1.8 expression in roots and leaves enhanced NO3- translocation to the aboveground. NR and GS activity in roots and leaves of Kronos was higher by increasing the expression of TANIA2, TAGS1, and TAGS2, which enhanced the reduction and assimilation of NO3- as well as the re-assimilation of photorespiratory-released NH4+. Overall, Kronos had strong N uptake, translocation, and assimilation capacity under N deficit stress, alleviating growth inhibition and plant N loss and thus maintaining a healthy development. This study reveals the physiological mechanisms of tetraploid wheat that improve nitrogen uptake and assimilation adaptation under low N stress, which will provide indispensable germplasm resources for elite low-N-tolerant wheat improvement and breeding.

Emmer wheat (Triticum dicoccum Schuebl.) favours high photosynthetic capacity adaptation to low nitrogen stress.

Although tetraploid wheat has rich genetic variability for cultivar improvement, its physiological mechanisms associated with photosynthetic productivity and resilience under nitrogen (N) deficit stress have not been investigated. In this study, we selected emmer wheat (Kronos, tetraploid), Yangmai 25 (YM25, hexaploid), and Chinese Spring (CS, hexaploid) as materials and investigated the differences in net photosynthetic rate (Pn), carboxylation capacity, electron transfer capacity, photosynthetic product output, and photosynthetic N allocation under normal N (CK) and low N (LN) through hydroponic experiments. Tetraploid emmer wheat (Kronos) had a stronger photosynthetic capacity than hexaploid wheat (YM25, CS) under low N stress, which mainly associated with the higher degree of PSII opening, electron transfer rate, Rubisco content and activity, ATP/ADP ratio, Rubisco activase (Rca) activity and Rubisco activation state, and more leaves N allocation to the photosynthetic apparatus, especially the proportion of N allocation to carboxylation under low N stress. Moreover, Kronos reduced the feedback inhibition of photosynthesis by sucrose accumulation through higher sucrose phosphate synthetase (SPS) activity and triose phosphate utilization rate (VTPU). Overall, Kronos could allocate more N to the photosynthetic components to improve Rubisco content and activity to maintain photosynthetic capacity under low N stress while enhancing triose phosphate output to reduce feedback inhibition of photosynthesis. This study reveals the physiological mechanisms of emmer wheat that maintain the photosynthetic capacity under low N stress, which will provide indispensable germplasm resources for elite low-N-tolerant wheat improvement and breeding.

Transforming waste into valuables: Preparation and evaluation of dual-ligand hydrophobic charge-induction chromatography using two poor performing ligands.

In conventional chromatographic ligand screening, underperforming ligands are often dismissed. However, this practice may inadvertently overlook potential opportunities. This study aims to investigate whether these underperforming ligands can be repurposed as valuable assets. Hydrophobic charge-induction chromatography (HCIC) is chosen as the validation target for its potential as an innovative chromatographic mode. A novel dual-ligand approach is employed, combining two suboptimal ligands (5-Aminobenzimidazole and Tryptamine) to explore enhanced performance and optimization prospects. Various dual-ligand HCIC resins with different ligand densities were synthesized by adjusting the ligand ratio and concentration. The resins were characterized to assess appearance, functional groups, and pore features using SEM, FTIR, and ISEC techniques. Performance assessments were conducted using single-ligand mode resins as controls, evaluating the selectivity against human immunoglobulin G and human serum albumin. Static adsorption experiments were performed to understand pH and salt influence on adsorption. Breakthrough experiments were conducted to assess dynamic adsorption capacity of the novel resin. Finally, chromatographic separation using human serum was performed to evaluate the purity and yield of the resin. Results indicated that the dual-ligand HCIC resin designed for human antibodies demonstrates exceptional selectivity, surpassing not only single ligand states but also outperforming certain high-performing ligand types, particularly under specific salt and pH conditions. Ultimately, a high yield of 83.9 % and purity of 96.7 % were achieved in the separation of hIgG from human serum with the dual-ligand HCIC, significantly superior to the single-ligand resins. In conclusion, through rational design and proper operational conditions, the dual-ligand mode can revitalize underutilized ligands, potentially introducing novel and promising chromatographic modes.

Genome-Wide Identification and Expression Analysis of TGA Family Genes Associated with Abiotic Stress in Sunflowers (Helianthus annuus L.).

Sunflower (Helianthus annuus L.) is an important, substantial global oil crop with robust resilience to drought and salt stresses. The TGA (TGACG motif-binding factor) transcription factors, belonging to the basic region leucine zipper (bZIP) family, have been implicated in orchestrating multiple biological processes. Despite their functional significance, a comprehensive investigation of the TGA family's abiotic stress tolerance in sunflowers remains elusive. In the present study, we identified 14 TGA proteins in the sunflower genome, which were unequally distributed across 17 chromosomes. Employing phylogenetic analysis encompassing 149 TGA members among 13 distinct species, we revealed the evolutionary conservation of TGA proteins across the plant kingdom. Collinearity analysis suggested that both HaTGA01 and HaTGA03 were generated due to HaTGA08 gene duplication. Notably, qRT-PCR analysis demonstrated that HaTGA04, HaTGA05, and HaTGA14 genes were remarkably upregulated under ABA, MeJA, and salt treatments, whereas HaTGA03, HaTGA06, and HaTGA07 were significantly repressed. This study contributes valuable perspectives on the potential roles of the HaTGA gene family under various stress conditions in sunflowers, thereby enhancing our understanding of TGA gene family dynamics and function within this agriculturally significant species.

Predicting the risk of lung cancer using machine learning: A large study based on UK Biobank.

In response to the high incidence and poor prognosis of lung cancer, this study tends to develop a generalizable lung-cancer prediction model by using machine learning to define high-risk groups and realize the early identification and prevention of lung cancer. We included 467,888 participants from UK Biobank, using lung cancer incidence as an outcome variable, including 49 previously known high-risk factors and less studied or unstudied predictors. We developed multivariate prediction models using multiple machine learning models, namely logistic regression, naïve Bayes, random forest, and extreme gradient boosting models. The performance of the models was evaluated by calculating the areas under their receiver operating characteristic curves, Brier loss, log loss, precision, recall, and F1 scores. The Shapley additive explanations interpreter was used to visualize the models. Three were ultimately 4299 cases of lung cancer that were diagnosed in our sample. The model containing all the predictors had good predictive power, and the extreme gradient boosting model had the best performance with an area under curve of 0.998. New important predictive factors for lung cancer were also identified, namely hip circumference, waist circumference, number of cigarettes previously smoked daily, neuroticism score, age, and forced expiratory volume in 1 second. The predictive model established by incorporating novel predictive factors can be of value in the early identification of lung cancer. It may be helpful in stratifying individuals and selecting those at higher risk for inclusion in screening programs.

Sex-specific associations of environmental exposures with prevalent diabetes and obesity - Results from the KORA Fit study.

Promising evidence suggests a link between environmental factors, particularly air pollution, and diabetes and obesity. However, it is still unclear whether men and women are equally susceptible to environmental exposures. Therefore, we aimed to assess sex-specific long-term effects of environmental exposures on metabolic diseases. We analyzed cross-sectional data from 3,034 participants (53.7% female, aged 53-74 years) from the KORA Fit study (2018/19), a German population-based cohort. Environmental exposures, including annual averages of air pollutants [nitrogen oxides (NO2, NOx), ozone, particulate matter of different diameters (PM10, PMcoarse, PM2.5), PM2.5abs, particle number concentration], air temperature and surrounding greenness, were assessed at participants' residences. We evaluated sex-specific associations of environmental exposures with prevalent diabetes, obesity, body-mass-index (BMI) and waist circumference using logistic or linear regression models with an interaction term for sex, adjusted for age, lifestyle factors and education. Further effect modification, in particular by urbanization, was assessed in sex-stratified analyses. Higher annual averages of air pollution, air temperature and greenness at residence were associated with diabetes prevalence in men (NO2: Odds Ratio (OR) per interquartile range increase in exposure: 1.49 [95% confidence interval (CI): 1.13, 1.95], air temperature: OR: 1.48 [95%-CI: 1.15, 1.90]; greenness: OR: 0.78 [95%-CI: 0.59, 1.01]) but not in women. Conversely, higher levels of air pollution, temperature and lack of greenness were associated with lower obesity prevalence and BMI in women. After including an interaction term for urbanization, only higher greenness was associated with higher BMI in rural women, whereas higher air pollution was associated with higher BMI in urban men. To conclude, we observed sex-specific associations of environmental exposures with metabolic diseases. An additional interaction between environmental exposures and urbanization on obesity suggests a higher susceptibility to air pollution among urban men, and higher susceptibility to greenness among rural women, which needs corroboration in future studies.

DcERF109 regulates shoot branching by participating in strigolactone signal transduction in Dendrobium catenatum.

Shoot branching fundamentally influences plant architecture and agricultural yield. However, research on shoot branching in Dendrobium catenatum, an endangered medicinal plant in China, remains limited. In this study, we identified a transcription factor DcERF109 as a key player in shoot branching by regulating the expression of strigolactone (SL) receptors DWARF 14 (D14)/ DECREASED APICAL DOMINANCE 2 (DAD2). The treatment of D. catenatum seedlings with GR24rac/TIS108 revealed that SL can significantly repress the shoot branching in D. catenatum. The expression of DcERF109 in multi-branched seedlings is significantly higher than that of single-branched seedlings. Ectopic expression in Arabidopsis thaliana demonstrated that overexpression of DcERF109 resulted in significant shoot branches increasing and dwarfing. Molecular and biochemical assays demonstrated that DcERF109 can directly bind to the promoters of AtD14 and DcDAD2.2 to inhibit their expression, thereby positively regulating shoot branching. Inhibition of DcERF109 by virus-induced gene silencing (VIGS) resulted in decreased shoot branching and improved DcDAD2.2 expression. Moreover, overexpression of DpERF109 in A. thaliana, the homologous gene of DcERF109 in Dendrobium primulinum, showed similar phenotypes to DcERF109 in shoot branch and plant height. Collectively, these findings shed new insights into the regulation of plant shoot branching and provide a theoretical basis for improving the yield of D. catenatum.

Development and validation of a nomogram to predict intracranial haemorrhage in neonates.

BACKGROUND: The aim of this study was to establish and validate a Susceptibility-weighted imaging (SWI)-based predictive model for neonatal intracranial haemorrhage (ICH). METHODS: A total of 1190 neonates suspected of ICH after cranial ultrasound screening in a tertiary hospital were retrospectively enrolled. The neonates were randomly divided into a training cohort and a internal validation cohort by a ratio of 7:3. Univariate analysis was used to analyze the correlation between risk factors and ICH, and the prediction model of neonatal ICH was established by multivariate logistic regression based on minimum Akaike information criterion (AIC). The nomogram was externally validated in another tertiary hospital of 91 neonates. The performance of the nomogram was evaluated in terms of discrimination by the area under the curve (AUC), calibration by the calibration curve and clinical net benefit by the decision curve analysis (DCA). RESULTS: Univariate analysis and min AIC-based multivariate logistic regression screened the following variables to establish a predictive model for neonatal ICH: Platelet count (PLT), gestational diabetes, mode of delivery, amniotic fluid contamination, 1-min Apgar score. The AUC was 0.715, 0.711, and 0.700 for the training cohort, internal validation cohort, and external validation cohort, respectively. The calibration curve showed a good correlation between the nomogram prediction and actual observation for ICH. DCA showed the nomogram was clinically useful. CONCLUSION: We developed and validated an easy-to-use nomogram to predict ICH for neonates. This model could support individualized risk assessment and healthcare.

A Pyroglutamate Aminopeptidase 1 Responsive Fluorescence Imaging Probe for Real-Time Rapid Differentiation between Thyroiditis and Thyroid Cancer.

Current diagnostic methods for thyroid diseases, including blood tests, ultrasound, and biopsy, always have difficulty diagnosing thyroiditis accurately, occasionally mistaking it for thyroid cancer. To address this clinical challenge, we developed Ox-PGP1, a novel fluorescent probe realizing rapid, noninvasive, and real-time diagnostic techniques. This is the first imaging tool capable of noninvasively distinguishing between thyroiditis and thyroid cancer. Ox-PGP1 was introduced as a fluorescent probe custom-built for the specific detection and quantification of pyroglutamate aminopeptidase 1 (PGP-1), a known pivotal biomarker of inflammation. Ox-PGP1 overcame the disadvantages of traditional enzyme-responsive fluorescent probes that relied on the intramolecular charge transfer (ICT) mechanism, including the issue of high background fluorescence, while offering exceptional photostability under laser irradiation. The spectral properties of Ox-PGP1 were meticulously optimized to enhance its biocompatibility. Furthermore, the low limit of detection (LOD) of Ox-PGP1 was determined to be 0.09 µg/mL, which demonstrated its remarkable sensitivity and precision. Both cellular and in vivo experiments validated the capacity of Ox-PGP1 for accurate differentiation between normal, inflammatory, and cancerous thyroid cells. Furthermore, Ox-PGP1 showed the potential to rapidly and sensitively differentiate between autoimmune thyroiditis and anaplastic thyroid carcinoma in a mouse model, achieving results in just 5 min. The successful design and application of Ox-PGP1 represent a substantial advancement in technology over traditional diagnostic approaches, potentially enabling earlier interventions for thyroid diseases.

Quantitative assessment whole-rock iron content in magnetite protolith based on terahertz time-domain spectroscopy.

Terahertz time-domain spectroscopy was first used to establish a correlation with the whole-rock iron (TFe) content in different depths of the Bayan Obo protolith. Compared with element content obtained by the traditional method of X-ray fluorescence spectroscopy (XRF), a similar tendency of the absorption coefficient and refractive index is presented. Furthermore, three machine learning algorithms, namely, partial least squares regression (PLSR), random forest (RF), and multi-layer perceptron (MLP), were used to develop a quantitative analytical model for TFe content of the protolith minerals. Among the three algorithms, MLP has the highest detection accuracy, with a model coefficient of determination R 2 reaching up to 0.945. These findings demonstrate that terahertz time-domain spectroscopy can be used to rapidly quantify the TFe elemental content of protolith, providing a method of detecting the content of mineral components.

Time-varying propagation model and dynamic-feedback-phase correction for multiplexed orbital angular momentum beams in atmospheric turbulence.

Freespace optical (FSO) communication in an outdoor setting is complicated by atmospheric turbulence (AT). A time-varying (TV) multiplexed orbital angular momentum (OAM) propagation model to consider AT under transverse-wind conditions is formulated for the first time, and optimized dynamic correction periods for various TV AT situations are found to improve the transmission efficiency. The TV nature of AT has until now been neglected from modeling of OAM propagation models, but it is shown to be important. First, according to the Taylor frozen-turbulence hypothesis, a series of AT phase screens influenced by transverse wind are introduced into the conventional angular-spectrum propagation analysis method to model both the temporal and spatial propagation characteristics of multiplexed OAM beams. Our model shows that while in weak TV AT, the power standard deviation of lower-order modes is usually smaller than that of higher-order modes, the phenomena in strong TV AT are qualitatively different. Moreover, after analyzing the effective time of each OAM phase correction, optimized dynamic correction periods for a dynamic feedback communication link are obtained. An optimized result shows that, under the moderate TV AT, both a system BER within the forward-error-correction limit and a low iterative computation volume with 6% of the real-time correction could be achieved with a correction period of 0.18 s. The research emphasizes the significance of establishing a TV propagation model for exploring the effect of TV AT on multiplexed OAM beams and proposing an optimized phase-correction mechanism to mitigate performance degradation caused by TV AT, ultimately enhancing overall transmission efficiency.

Passive localization and reconstruction of multiple non-line-of-sight objects in a scene with a large visible transmissive window.

Passive non-line-of-sight imaging methods have been demonstrated to be capable of reconstructing images of hidden objects. However, current passive non-line-of-sight imaging methods have performance limitations due to the requirements of an occluder and aliasing between multiple objects. In this paper, we propose a method for passive localization and reconstruction of multiple non-line-of-sight objects in a scene with a large visible transmissive window. The analysis of the transport matrix revealed that more redundant information is acquired in a scene with a window than that with an occluder, which makes the image reconstruction more difficult. We utilized the projection operator and residual theory to separate the reconstruction equation of multiple objects into the independent equations of the located objects that can be reconstructed independently by TVAL3 and Split-Bregman algorithms, which greatly reduces the computational complexity of the reconstruction. Our method lays the foundation for multiple objects reconstruction in complex non-line-of-sight scenes.

Heat and Cardiovascular Mortality: An Epidemiological Perspective.

As global temperatures rise, extreme heat events are projected to become more frequent and intense. Extreme heat causes a wide range of health effects, including an overall increase in morbidity and mortality. It is important to note that while there is sufficient epidemiological evidence for heat-related increases in all-cause mortality, evidence on the association between heat and cause-specific deaths such as cardiovascular disease (CVD) mortality (and its more specific causes) is limited, with inconsistent findings. Existing systematic reviews and meta-analyses of epidemiological studies on heat and CVD mortality have summarized the available evidence. However, the target audience of such reviews is mainly limited to the specific field of environmental epidemiology. This overarching perspective aims to provide health professionals with a comprehensive overview of recent epidemiological evidence of how extreme heat is associated with CVD mortality. The rationale behind this broad perspective is that a better understanding of the effect of extreme heat on CVD mortality will help CVD health professionals optimize their plans to adapt to the changes brought about by climate change and heat events. To policymakers, this perspective would help formulate targeted mitigation, strengthen early warning systems, and develop better adaptation strategies. Despite the heterogeneity in evidence worldwide, due in part to different climatic conditions and population dynamics, there is a clear link between heat and CVD mortality. The risk has often been found to be higher in vulnerable subgroups, including older people, people with preexisting conditions, and the socioeconomically deprived. This perspective also highlights the lack of evidence from low- and middle-income countries and focuses on cause-specific CVD deaths. In addition, the perspective highlights the temporal changes in heat-related CVD deaths as well as the interactive effect of heat with other environmental factors and the potential biological pathways. Importantly, these various aspects of epidemiological studies have never been fully investigated and, therefore, the true extent of the impact of heat on CVD deaths remains largely unknown. Furthermore, this perspective also highlights the research gaps in epidemiological studies and the potential solutions to generate more robust evidence on the future consequences of heat on CVD deaths.

Biomarkers for neuromyelitis optica: a visual analysis of emerging research trends.

Neuromyelitis optica is an inflammatory demyelinating disease of the central nervous system that differs from multiple sclerosis. Over the past 20 years, the search for biomarkers for neuromyelitis optica has been ongoing. Here, we used a bibliometric approach to analyze the main research focus in the field of biomarkers for neuromyelitis optica. Research in this area is consistently increasing, with China and the United States leading the way on the number of studies conducted. The Mayo Clinic is a highly reputable institution in the United States, and was identified as the most authoritative institution in this field. Furthermore, Professor Wingerchuk from the Mayo Clinic was the most authoritative expert in this field. Keyword analysis revealed that the terms "neuromyelitis optica" (261 times), "multiple sclerosis" (220 times), "neuromyelitis optica spectrum disorder" (132 times), "aquaporin 4" (99 times), and "optical neuritis" (87 times) were the most frequently used keywords in literature related to this field. Comprehensive analysis of the classical literature showed that the majority of publications provide conclusive research evidence supporting the use of aquaporin-4-IgG and neuromyelitis optica-IgG to effectively diagnose and differentiate neuromyelitis optica from multiple sclerosis. Furthermore, aquaporin-4-IgG has emerged as a highly specific diagnostic biomarker for neuromyelitis optica spectrum disorder. Myelin oligodendrocyte glycoprotein-IgG is a diagnostic biomarker for myelin oligodendrocyte glycoprotein antibody-associated disease. Recent biomarkers for neuromyelitis optica include cerebrospinal fluid immunological biomarkers such as glial fibrillary acidic protein, serum astrocyte damage biomarkers like FAM19A5, serum albumin, and gamma-aminobutyric acid. The latest prospective clinical trials are exploring the potential of these biomarkers. Preliminary results indicate that glial fibrillary acidic protein is emerging as a promising candidate biomarker for neuromyelitis optica spectrum disorder. The ultimate goal of future research is to identify non-invasive biomarkers with high sensitivity, specificity, and safety for the accurate diagnosis of neuromyelitis optica.

Hypertension-specific association of cardio-ankle vascular index with subclinical left ventricular function in a Chinese population: Danyang study.

The association of cardio-ankle vascular index (CAVI), with subclinical cardiac dysfunction in hypertensive patients is unclear. We aim to examine their relationship in hypertensive patients compared with that in normotensive subjects. Our study included 1887 subjects enrolled from Danyang between 2018 and 2019. CAVI was measured using VaSera VS-1500A device. We performed conventional echocardiography to measure ejection fraction (EF) and E/A, tissue Doppler to measure mitral annular early diastolic velocities (e'), and speckle-tracking to estimate left ventricular (LV) global longitudinal strain (GLS). LV mass index (76.3, 80.0, and 84.0 g/m2), and E/e' (7.6, 8.2, and 8.8) were increased and GLS (21.1, 21.0, and 20.4%), E/A (1.2, 1.0, and 0.8) and e' velocity (11.2, 9.4, and 8.2 cm/s) was decreased from tertiles 1-3 of CAVI on unadjusted analyses (P < .001). After adjustment for covariates, GLS, E/A, and e' were still significantly decreased from tertiles 1-3 of CAVI (P ≤ .04). Further sensitive analyses revealed a similar association pattern for diastolic function but not systolic function. Compared with the lowest tertile, subjects with a top tertile of CAVI were at higher risk of subclinical LV systolic dysfunction in hypertensive patients (OR = 2.61; P = .005). Increased CAVI is associated with worse subclinical diastolic function. However, this relationship of CAVI to subclinical systolic function was more prominent in hypertensive patients.

Targeted Gene Insertion: The Cutting Edge of CRISPR Drug Development with Hemophilia as a Highlight.

The remarkable advance in gene editing technology presents unparalleled opportunities for transforming medicine and finding cures for hereditary diseases. Human trials of clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein-9 nuclease (Cas9)-based therapeutics have demonstrated promising results in disrupting or deleting target sequences to treat specific diseases. However, the potential of targeted gene insertion approaches, which offer distinct advantages over disruption/deletion methods, remains largely unexplored in human trials due to intricate technical obstacles and safety concerns. This paper reviews the recent advances in preclinical studies demonstrating in vivo targeted gene insertion for therapeutic benefits, targeting somatic solid tissues through systemic delivery. With a specific emphasis on hemophilia as a prominent disease model, we highlight advancements in insertion strategies, including considerations of DNA repair pathways, targeting site selection, and donor design. Furthermore, we discuss the complex challenges and recent breakthroughs that offer valuable insights for progressing towards clinical trials.

Asymmetric synthesis of P-stereogenic phosphindane oxides via kinetic resolution and their biological activity.

The importance of P-stereogenic heterocycles has been widely recognized with their extensive use as privileged chiral ligands and bioactive compounds. The catalytic asymmetric synthesis of P-stereogenic phosphindane derivatives, however, remains a challenging task. Herein, we report a catalytic kinetic resolution of phosphindole oxides via rhodium-catalyzed diastereo- and enantioselective conjugate addition to access enantiopure P-stereogenic phosphindane and phosphindole derivatives. This kinetic resolution method features high efficiency (s factor up to >1057), excellent stereoselectivities (all >20:1 dr, up to >99% ee), and a broad substrate scope. The obtained chiral phosphindane oxides exhibit promising therapeutic efficacy in autosomal dominant polycystic kidney disease (ADPKD), and compound 3az is found to significantly inhibit renal cyst growth both in vitro and in vivo, thus ushering in a promising scaffold for ADPKD drug discovery. This study will not only advance efforts towards the asymmetric synthesis of challenging P-stereogenic heterocycles, but also surely inspire further development of P-stereogenic entities for bioactive small-molecule discovery.

Systematic Engineering of Saccharomyces cerevisiae for the De Novo Biosynthesis of Genistein and Glycosylation Derivatives.

Isoflavones are predominantly found in legumes and play roles in plant defense and prevention of estrogen-related diseases. Genistein is an important isoflavone backbone with various biological activities. In this paper, we describe how a cell factory that can de novo synthesize genistein was constructed in Saccharomyces cerevisiae. Different combinations of isoflavone synthase, cytochrome P450 reductase, and 2-hydroxyisoflavone dehydratase were tested, followed by pathway multicopy integration, to stably de novo synthesize genistein. The catalytic activity of isoflavone synthase was enhanced by heme supply and an increased intracellular NADPH/NADP+ ratio. Redistribution of the malonyl-CoA flow and balance of metabolic fluxes were achieved by adjusting the fatty acid synthesis pathway, yielding 23.33 mg/L genistein. Finally, isoflavone glycosyltransferases were introduced into S. cerevisiae, and the optimized strain produced 15.80 mg/L of genistin or 10.03 mg/L of genistein-8-C-glucoside. This is the first de novo synthesis of genistein-8-C-glucoside in S. cerevisiae, which is advantageous for the green industrial production of isoflavone compounds.

Earthquake supercycles and fault interaction over the past 32 ka in the Lake Ebinur area, Xinjiang, China.

Earthquake prediction and disaster assessment in tectonically active regions require a continuous and complete regional seismic archive, which is commonly difficult to obtain, especially for prehistoric records. Here, high-resolution analysis of the sedimentary sequence from Lake Ebinur in Xinjiang revealed a detailed history of environment evolution since 32 ka ago. Both the Cl content and ultrafine proportion revealed the changing climate: the climate was relatively dry with low lake-water volumes from 32 to 12 ka, while the climate became warmer and wetter since 12 ka. In addition, eight earthquakes were identified by comprehensive analysis of grain size and geochemical element proxies, showing more than two seismic supercycles, with gaps of ∼10.4 ka; these gaps are much larger than those inferred previously (∼4-7 ka). Notably, these seismic events exhibited a pattern of mutual transmittance between the BoA and Jinghenan faults. Such fault interaction can occur in the Lake Ebinur area because it is dominated by weak lithosphere in which strain is easily accumulated and released; the interaction can also be attributed to the unique spatial distribution and immature nature of both faults. Combined with trenching investigations, our high-resolution analysis of lacustrine sediments can reveal a complete history of tectonic activity, which can efficiently serve regional earthquake prediction and disaster assessment.