Microfluidic Device with an Oxygen Gradient Generator for Investigating Effects of Specific Hypoxia Conditions on Responses of Tumor Cells.

The oxygen level in the tumor microenvironment (TME) plays a critical role in regulating cell fates such as proliferation, migration, apoptosis, and so forth. To better elucidate how hypoxia affects tumor cell behaviors, a series of microfluidic strategies have been utilized to generate an oxygen gradient covering both hypoxia anions. However, in most studies, some chemicals are introduced into microfluidic chips, causing the potential of their poor biocompatibility. The common oxygen gradient with linear variation does not allow the effects of specific oxygen concentrations on tumor cells to be analyzed accurately. In this paper, based on the physical method of gas diffusion, a microfluidic device integrated with an oxygen gradient generator is proposed for investigating effects of different hypoxia levels on responses of tumor cells. This device consists of three layers, i.e., upper layer, thin film layer, and bottom layer. The upper layer is used for introducing the initial gas and generating an oxygen gradient in the form of gas. The bottom layer is used for introducing cells and culture medium. The thin film layer separates the former two layers, allowing the gas to diffuse from the top to the bottom through it. The oxygen gradient in the bottom layer is finally generated in the form of dissolved oxygen. The device is fabricated using microfabrication technology. The effects of structural and working parameters of the device on the oxygen gradient are evaluated by finite element simulation. The oxygen gradient in cell culture channels is characterized by using oxygen-sensitive fluorescence materials. The proliferation and morphology of HeLa cells under specific oxygen levels are compared after culturing for 48 h. The oxygen gradient with a ladder-like distribution demonstrates that this microfluidic device can provide a prospective experimental platform for in vitro cell studies and revelation of the mechanism of tumor metastasis associated with a specific hypoxic microenvironment.

ZmCRK1 negatively regulates maize's response to drought stress by phosphorylating plasma membrane H+-ATPase ZmMHA2.

Drought severely affects crop growth and yields. Stomatal regulation plays an important role in plant response to drought stress. Light-activated plasma membrane-localized proton ATPase (PM H+-ATPase) mainly promoted the stomatal opening. Abscisic acid (ABA) plays a dominant role in the stomatal closure during drought stress. It is not clear how PM H+-ATPase is involved in the regulation of ABA-induced stomatal closure. We found that a CALCIUM-DEPENDENT PROTEIN KINASE RELATED KINASE 1 (ZmCRK1), and its mutant zmcrk1 exhibited slow water loss in detached leaves, high-survival rate after drought stress, and sensitivity to stomatal closure induced by ABA. The ZmCRK1 overexpression lines are opposite. ZmCRK1 interacted with the maize PM H+-ATPase ZmMHA2. ZmCRK1 phosphorylated ZmMHA2 at the Ser-901 and inhibited its proton pump activity. ZmCRK1 overexpression lines and zmmha2 mutants had low H+-ATPase activity, resulting in impaired ABA-induced H+ efflux. Taken together, our study indicates that ZmCRK1 negatively regulates maize drought stress response by inhibiting the activity of ZmMHA2. Reducing the expression level of ZmCRK1 has the potential to reduce yield losses under water deficiency.

[Molecular study of a case with variant of RHCE*ce allele in haplotype dce resulting in weakened e antigen].

OBJECTIVE: To explore the Rh genotype for a female with RhD(-) blood type and its molecular basis. METHODS: A 26-year-old female who had attended the outpatient clinic of the First Affiliated Hospital of Zhengzhou University in August 2019 was selected as the study subject. Peripheral blood samples were collected from the proband and her parents for Rh phenotyping with gel card method. PCR-sequence-based typing (PCR-SBT) and DNA sequencing were used to determine the RHD zygosity and Rh genotype of the proband and her parents. Homology modeling of Rh proteins was performed with bioinformatic software, and protein structural alterations caused by the variant was simulated by molecular dynamics. RESULTS: Serological tests showed that the proband and her father both had weakened e antigen of the Rh phenotype. PCR-SBT and DNA sequencing showed that the genotypes of the proband and her parents were dce/dCE, dce/DcE and dCE/DcE, respectively. And the genotypes of the RHD and RHCE of the proband were RHD*01N.01/RHD*01N.16, RHCE*01.01/RHCE*04, respectively. Protein simulation and molecular dynamics analysis revealed that the ce_16C variant resulted from RHCE*ce (c.48G>C) may alter the structure of intracellular and extracellular loops, mainly affecting the mobility of extracellular loops 2, 6 and intracellular loops 3, 4. CONCLUSION: Variant of the RHCE*ce allele c.48G>C probably underlay the weakened e antigen in this proband.

Development and Validation of a Nomogram for Predicting Acute Kidney Injury in Septic Patients.

Purpose: Sepsis-associated acute kidney injury (S-AKI) is associated with increased morbidity and mortality. We aimed to develop a nomogram for predicting the risk of S-AKI patients. Patients and Methods: We collected data from septic patients admitted to the Provincial Hospital Affiliated with Shandong First Medical University from January 2019 to September 2022. Septic patients were divided into two groups based on the occurrence of AKI. A nomogram was developed by multiple logistic regression analyses. The performance of the nomogram was evaluated using C-statistics, calibration curves, and decision curve analysis (DCA). The validation cohort contained 70 patients between December 2022, and March 2023 in the same hospital. Results: 198 septic patients were enrolled in the training cohort. Multivariate logistic regression analysis showed that neutrophil gelatinase-associated lipocalin (NGAL), platelet-to-lymphocyte ratio (PLR), and vasopressor use were independent risk factors for S-AKI. A nomogram was developed based on these factors. C-statistics for the training and validation cohorts were respectively 0.873 (95% CI 0.825-0.921) and 0.826 (95% CI 0.727-0.924), indicating high prediction accuracy. The calibration curves showed good concordance. DCA revealed that the nomogram was of great clinical value. Conclusion: The nomogram presents early and effective prediction for the S-AKI patients, and provides optimal intervention to improve patient outcomes.

Ferroptosis in liver diseases: Fundamental mechanism and clinical implications.

This editorial discusses a recently published paper in the World Journal of Gastroenterology. Our research focuses on p53's regulatory mechanism for controlling ferroptosis, as well as the intricate connection between ferroptosis and liver diseases. Ferroptosis is a specific form of programmed cell death that is de-pendent on iron and displays unique features in terms of morphology, biology, and genetics, distinguishing it from other forms of cell death. Ferroptosis can affect the liver, which is a crucial organ responsible for iron storage and meta-bolism. Mounting evidence indicates a robust correlation between ferroptosis and the advancement of liver disorders. P53 has a dual effect on ferroptosis through various distinct signaling pathways. However, additional investigations are required to clarify the regulatory function of p53 metabolic targets in this complex association with ferroptosis. In the future, researchers should clarify the mechanisms by which ferroptosis and other forms of programmed cell death contribute to the progression of liver diseases. Identifying and controlling important regulatory factors associated with ferroptosis present a promising therapeutic strategy for liver disorders.

Unveiling Influences of metal-based nanomaterials on wheat growth and physiology: From benefits to detriments.

Metal-based nanomaterials (MNs) are widely used in agricultural production. However, our current understanding of the overall effects of MNs on crop health is insufficient. A global meta-analysis of 144 studies involving approximately 2,000 paired observations was conducted to explore the impacts of MNs on wheat growth and physiology. Our analysis revealed that the MN type plays a key role in influencing wheat growth. Ag MNs had significant negative effects on wheat growth and physiology, whereas Fe, Ti, and Zn MNs significantly increased wheat biomass and photosynthesis. Our study also observed a clear dose-specific effect, with a decrease in wheat shoot biomass with increasing MN concentrations. Meanwhile, MNs with small sizes (< 25 nm) have no significant impacts on wheat growth. Furthermore, both the root and foliar applications significantly improved wheat growth, with no considerable differences. Using a machine learning approach, we found that the MN type was the main driving factor affecting wheat shoot biomass, followed by MN dose and size. Overall, wheat growth and physiology can be negatively influenced by specific MNs, for which a high dose and small size should be avoided in practical applications. Therefore, our study can provide insights into the future design and safe use of MNs in agriculture and increase the public acceptance of nano-agriculture.

Efficacy of a health education technology program in improving adherence to self-management behaviors and quality of life among adults with type 2 diabetes: A randomized controlled trial.

AIM: This study examined the efficacy of a health education technology program on self-management adherence behavior and quality of life among people with type 2 diabetes (T2D). METHODS: A randomized experimental study design was employed. A total of 110 subjects was recruited. The experimental group received a novel technology education program plus routine shared care. The control group received routine shared care alone. Quality of life and adherence to self-management behavior questionnaires were used to measure outcomes. A linear mixed-effects model was used to analyze changes in quality of life after controlling for pre-test effects. The odds ratio was calculated for differences in adherence behavior between the two groups. RESULTS: The between-group mean difference in quality of life scores and adherence to physical activity comparing pre-test at 3 months follow-up showed significant progress at 3 months post-test compared with the control group. However, the increase in mean quality of life scores and adherence behavior at 6 months did not demonstrate a sustained between-group difference. CONCLUSION: The results showed adherence to physical activity and improved quality of life in patients with T2D at 3 months post intervention. Therefore, the program can be used as an intensive model for diabetes shared care.

Squaraine-Linked Magnetic Covalent Organic Framework as a Solid-Phase Extraction Absorbent to Determine Trace Phenylpyrazoles.

Phenylpyrazoles are widely used pesticides in the food industry. It is highly desirable to develop efficient pre-treatment and analysis methods to extract and detect phenylpyrazoles in complex food matrices. Herein, the study reports novel squaraine-linked zwitterionic core-shell magnetic covalent organic frameworks (MCOFs),  which are found to be excellent pretreatment materials for the detection of trace phenylpyrazoles in samples. By coupling MCOFs to magnetic solid-phase extraction (MSPE) with Ultra Performance Liquid Chromatography-Tandem Mass Spectrometry (UPLC-MS/MS) analysis, the detection of phenylpyrazoles (fipronil, fipronil sulfone, fipronil sulfide, fipronil de-sulfoxide, fipronil desulfinyl, ethiprole, and flufiprole) is achieved and shows good linearity at concentrations of 1-800 µg L-1 (R2 ≥ 0.9930). The limit of detection (LOD), limit of quantification (LOQ), and recovery rates are 0.01-0.50 µg kg-1, 0.04-1.72 µg kg-1, and 70.96-115.32%, respectively. More importantly, this method is successfully applied to determine the phenylpyrazoles in commercial egg, poultry, milk, jujube, cabbage, tea, and rice with a detection rate of ≈0.04%. Therefore, the developed method may contribute to a new strategy for the purification and multi-target extraction of complex food matrices.

Design and characteristics of a fiber laser powered repetitive micro-plasma jet triggered gas switch.

To satisfy the need for low jitter in gas switches at repetition rate and enhance insulation reliability during high voltage operation of the trigger, we propose a micro-jet triggering system. This system requires less energy and can use a laser power supply as an energy source. It effectively improves the insulation stability of the trigger when working at high potentials and achieves a good triggering effect with low jitter at low working coefficients. The breakdown characteristics were tested by double-pulse experiments. Ensuring the same operating conditions for both pulses, the pulse interval was varied to obtain the breakdown voltage dispersion at different repetition rates. The results indicate that the dispersion of the breakdown voltages can reach 0.16% at a frequency of 50 Hz with a pulse front of 30 µs, representing an order of magnitude reduction compared to the 1.45% at switching self-breakdown, and decreases further as the air pressure rises. In addition, the size of the microcapillary has an impact on the dispersion of breakdown voltage. It was found that for a range of lengths from 2 to 6 mm and aperture sizes from 80 to 400 µm, the trigger jitter was lower when the length was larger and the aperture was smaller. Furthermore, a trigger life test was performed on the ceramic capillary, and after one million triggers, the system remained stable with no degradation in trigger performance.

Abalone shells bioenhanced carboxymethyl chitosan/collagen/PLGA bionic hybrid scaffolds achieving biomineralization and osteogenesis for bone regeneration.

Inspired by the formation of natural abalone shells (AS) similar to calcium salt deposition in human orthodontics, AS is used as an emulsifier in the scaffold to solve the problem of coexistence of natural and synthetic polymers and promote new bone formation. In this study, AS-stabilized and reinforced carboxymethyl chitosan/collagen/PLGA porous bionic composite scaffolds (AS/CMCS/Col/PLGA) were fabricated through the emulsion polymerization and bionic hybrid technology. As the addition of AS increased from 0.75 to 3.0 wt%, homogeneous distribution of flower-like particles could be observed on the inner surface of the scaffold, and its mechanical properties were improved. Particularly, 3.0 wt% AS-doped scaffolds (S3 and C + S3) exhibited excellent inorganic mineral deposition and osteoblast proliferation and differentiation abilities in vitro. In a SD rat calvarial defect model, they effectively promoted new bone formation in the defect and accelerated expression of osteogenic-angiogenic related proteins (COLI, OCN, VEGF). By virtue of its combined merits including good mechanical properties, inducing mineralization crystallization and facilitating osteogenesis, the 3.0 wt% AS-doped scaffold promises to be employed as a novel bone repair material for bone tissue regeneration.

Heritability and Genetic Factors of Astigmatism and Corneal Curvature: a Systematic Review and Meta-analysis.

PURPOSE: To systematically review and meta-analyze all reported heritability studies of refractive astigmatism (RA), corneal astigmatism (CA) and corneal curvature (CC), and evaluate the existing genetic associations of RA, CA and CC. DESIGN: Systematic review and meta-analysis (PROSPERO ID: CRD42023447370). METHODS: Studies that reported the heritability and genetic associations of RA, CA and/or CC were identified from PubMed, Web of Science and EMBASE (from inception to October 1, 2023). Newcastle-Ottawa Scale criteria was used to assess the risk of bias. Meta-analyses of heritability were conducted using random-effects model for mean difference. All current genetic associations were catalogued according to level of statistical significance. RESULTS: Pooled heritabilities were moderate for RA (h2 = 0.46, 95% CI: 0.27 - 0.65), CA (h2 = 0.48, 95% CI: 0.38 - 0.58) and CC (h2 = 0.64, 95% CI: 0.53 - 0.76). Subgroup analyses revealed significant differences between analysis methods (CA: P < 0.01; CC: P = 0.03) and populations (CA: P < 0.01; CC: P < 0.01) in both CA and CC, and between age groups in CA (P < 0.01). Totally 50 single-nucleotide polymorphisms (SNPs) in 10 genes have been reported with overlapping associations with RA, CA and/or CC, with BMP3, FMNL2, HERC2, PROX1-AS1 and ZC3H11B associated with RA and CA, FBN1, NHSL1 and PDGFRA with CA and CC, TRAF3IP1 with RA and CC; and CASC15 with RA, CA and CC. CONCLUSIONS: This study confirms moderate heritabilities of RA, CA and CC. Through evaluating overlapping SNPs or genes between these three phenotypes, we prioritized 50 SNPs in 10 genes as candidate variants for further validation. These findings highlight the complex genetic architecture of astigmatism and indicate shared and distinct genetic markers for different astigmatism-related corneal parameters. Future studies in different populations and functional studies evaluating the roles of the involved genes in astigmatism are warranted.

Post-hoc analysis of clinicopathological factors affecting lateral lymph node metastasis based on STELLAR study for rectal cancer.

PURPOSE: In post-hoc analyses of phaseIII randomized controlled study(STELLAR), to analyzethe prognostic impact oflateral pelvic lymph node (LPLN)metastasis in locally advanced rectal cancer (LARC). METHODS: LPLN metastasis was defined as a short diameter > 7 mm on magnetic resonance imaging (MRI).The studyincluded 591 patients with LARC.All patients received neoadjuvant (chemo)radiotherapy combined withradical resection. RESULTS: Among 591 patients, 99 (16.8 %) were diagnosed with LPLN metastasis, mostly with unilateral metastasis (79.8 %), with internal iliac lymph node metastasis being more common (81.8 %).Significant differences were found among with and without LPLN metastasis in rectal segmentation (P=0.001),N disease (P<0.001), mesenteric LN metastasis or not (P=0.030). The median follow-up timewas 34.0 months, three-year disease-free survival (DFS),overall survival (OS), andmetastasis-free survival (MFS)were significantly lower in LPLN metastaticgroup than those in LPLN non-metastaticgroup (51.4 % vs. 68.2 %, P<0.001; 71.8 % vs. 84.2 %, P=0.006; 60.8 % vs. 80.1 %,P<0.001), respectively; while there were no significant differences in locoregional recurrence(11.4 % vs. 8.5 %, P=0.564). Multivariate analysis found that LPLN metastasis was an independent prognostic factor affecting DFS (P=0.005), OS (P=0.036),MFS (P=0.001).No significantly survival benefit was observed for the short-term radiotherapy based total neoadjuvant therapy compared to long-term concurrent chemoradiotherapy. CONCLUSIONS: LPLN metastasis observed byMRI should be considered in LARC patients, especially in populations with lowrectal cancer, N2 disease, and mesenteric LN metastasis. LPLN metastasis diagnosed by MRI is a significant and independent risk factor and is associated with worse DFS, OS, MFS.

Deep5hmC: Predicting genome-wide 5-Hydroxymethylcytosine landscape via a multimodal deep learning model.

MOTIVATION: 5-hydroxymethylcytosine (5hmC), a crucial epigenetic mark with a significant role in regulating tissue-specific gene expression, is essential for understanding the dynamic functions of the human genome. Despite its importance, predicting 5hmC modification across the genome remains a challenging task, especially when considering the complex interplay between DNA sequences and various epigenetic factors such as histone modifications and chromatin accessibility. RESULTS: Using tissue-specific 5hmC sequencing data, we introduce Deep5hmC, a multimodal deep learning framework that integrates both the DNA sequence and epigenetic features such as histone modification and chromatin accessibility to predict genome-wide 5hmC modification. The multimodal design of Deep5hmC demonstrates remarkable improvement in predicting both qualitative and quantitative 5hmC modification compared to unimodal versions of Deep5hmC and state-of-the-art machine learning methods. This improvement is demonstrated through benchmarking on a comprehensive set of 5hmC sequencing data collected at four developmental stages during forebrain organoid development and across 17 human tissues. Compared to DeepSEA and random forest, Deep5hmC achieves close 4 % and 17% improvement of AUROC across four forebrain developmental stages, and 6% and 27% across 17 human tissues for predicting binary 5hmC modification sites; and 8% and 22% improvement of Spearman correlation coefficient across four forebrain developmental stages, and 17% and 30% across 17 human tissues for predicting continuous 5hmC modification. Notably, Deep5hmC showcases its practical utility by accurately predicting gene expression and identifying differentially hydroxymethylated regions in a case-control study of Alzheimer's disease. Deep5hmC significantly improves our understanding of tissue-specific gene regulation and facilitates the development of new biomarkers for complex diseases. AVAILABILITY AND IMPLEMENTATION: Deep5hmC is available via https://github.com/lichen-lab/Deep5hmC. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Linkage Mapping and Discovery of Candidate Genes for Drought Tolerance in Rice During the Vegetative Growth Period.

Drought is a major abiotic stress affecting crop yields. Mapping quantitative trait loci (QTLs) and mining genes for drought tolerance in rice are important for identifying gene functions and targets for molecular breeding. Here, we performed linkage analysis of drought tolerance using a recombinant inbred line population derived from Jileng 1 (drought sensitive) and Milyang 23 (drought tolerant). An ultra-high-density genetic map, previously constructed by our research team using genotype data from whole-genome sequencing, was used in combination with phenotypic data for rice grown under drought stress conditions in the field in 2017-2019. Thirty-nine QTLs related to leaf rolling index and leaf withering degree were identified, and QTLs were found on all chromosomes except chromosomes 6, 10, and 11. qLWD4-1 was detected after 32 days and 46 days of drought stress in 2017 and explained 7.07-8.19% of the phenotypic variation. Two loci, qLRI2-2 and qLWD4-2, were identified after 29, 42, and 57 days of drought stress in 2018. These loci explained 10.59-17.04% and 5.14-5.71% of the phenotypic variation, respectively. There were 281 genes within the QTL interval. Through gene functional annotation and expression analysis, two candidate genes, Os04g0574600 and OsCHR731, were found. Quantitative reverse transcription PCR analysis showed that the expression levels of these genes were significantly higher under drought stress than under normal conditions, indicating positive regulation. Notably, Os04g0574600 was a newly discovered drought tolerance gene. Haplotype analysis showed that the RIL population carried two haplotypes (Hap1 and Hap2) of both genes. Lines carrying Hap2 exhibited significantly or extremely stronger drought tolerance than those carrying Hap1, indicating that Hap2 is an excellent haplotype. Among rice germplasm resources, there were two and three haplotypes of Os04g0574600 and OsCHR731, respectively. A high proportion of local rice resources in Sichuan, Yunnan, Anhui, Guangdong and Fujian provinces had Hap of both genes. In wild rice, 50% of accessions contained Hap1 of Os04g0574600 and 50% carried Hap4; 13.51%, 59.46% and 27.03% of wild rice accessions contained Hap1, Hap2, and Hap3, respectively. Hap2 of Os04g0574600 was found in more indica rice resources than in japonica rice. Therefore, Hap2 has more potential for utilization in future drought tolerance breeding of japonica rice.

Deep learning-assisted segmentation of X-ray images for rapid and accurate assessment of foot arch morphology and plantar soft tissue thickness.

The morphological characteristics of the foot arch and the plantar soft tissue thickness are pivotal in assessing foot health, which is associated with various foot and ankle pathologies. By applying deep learning image segmentation techniques to lateral weight-bearing X-ray images, this study investigates the correlation between foot arch morphology (FAM) and plantar soft tissue thickness (PSTT), examining influences of age and sex. Specifically, we use the DeepLab V3+ network model to accurately delineate the boundaries of the first metatarsal, talus, calcaneus, navicular bones, and overall foot, enabling rapid and automated measurements of FAM and PSTT. A retrospective dataset containing 1497 X-ray images is analyzed to explore associations between FAM, PSTT, and various demographic factors. Our findings contribute novel insights into foot morphology, offering robust tools for clinical assessments and interventions. The enhanced detection and diagnostic capabilities provided by precise data support facilitate population-based studies and the leveraging of big data in clinical settings.

Spatial source, simulating improvement, and short-term health effect of high PM2.5 exposure during mutation event in the key urban agglomeration regions in China.

Air quality in China has significantly improved owing to the effective implementation of pollution control measures. However, mutation events caused by short-term spikes in PM2.5 in urban agglomeration regions continue to occur frequently. Identifying the spatial sources and influencing factors, as well as improving the prediction accuracy of high PM2.5 during mutation events, are crucial for public health. In this study, we firstly introduced discrete wavelet transform (DWT) to identify the mutation events with high PM2.5 concentration in the four key urban agglomerations, and evaluated the spatial sources for the polluted scenario using Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model. Additionally, DWT was combined with a widely used artificial neural network (ANN) to improve the prediction accuracy of PM2.5 concentration seven days in advance (seven-day forecast). Results indicated that mutation events commonly occurred in the northern regions during winter time, which were under the control of both short-range transportation of dirty airmass as well as negative meteorology conditions. Compared with the ANN model alone, the average band errors decreased by 9% when using DWT-ANN model. The average correlation coefficient (R) and root mean square error (RMSE) obtained using the DWT-ANN improved by 10% and 12% compared to those obtained using the ANN, indicating the efficiency and accuracy of simulating PM2.5, by combining the DWT and ANN. The short-term mortality during mutation events was then calculated, with the total averted all-cause, cardiovascular, and respiratory deaths in the four regions, being 4751, 2554, and 582 persons, respectively. A declining trend in prevented deaths from 2018 to 2020 demonstrated that the pollution intensity during mutation events gradually decreased owing to the implementation of the Three-Year Action Plan to Win the Blue Sky Defense War. The method proposed in this study can be used by policymakers to take preventive measures in response to a sudden increase in PM2.5, thereby ensuring public health.

Geneenvironment interaction between phthalate exposure and pubertal genetic polymorphisms on blood pressure variability in children: Exploring the moderating effects of lifestyle behaviours.

Phthalates (PAEs) are synthetic compounds extensively employed in consumer products. Blood pressure (BP) in children can vary, the degree of visit-to-visit BP variability (VVV) is at least partially independent of BP. The interactions between PAEs exposure, pubertal-related genetic susceptibility and lifestyles on childhood VVV are not investigated. This study utilized data from a cohort collected from Oct 2017-2020 in Xiamen, China. Seven urine PAE metabolites were measured. The long-term VVV was characterized employing the standard deviation (SD) and average real variability. We constructed a genetic risk score (GRS) of pubertal-related genes and healthy lifestyle scores. Exposed to high levels of mono-2-ethyl-5-hydroxyhexyl phthalate (MEHHP) (OR=1.43, 95 %CI=1.07, 1.92) and mono-2-ethyl-5-oxohexyl phthalate (OR=1.36, 95 % CI=1.01, 1.83) was related to increased SBP-SD, and the OR for high SBP-SD related to high GRS was 1.38 (95 % CI=1.02, 1.85). Compared to participants who had low GRS and low MEHHP exposure, participants exhibiting high GRS and MEHHP levels were more likely to experience high SBP-SD (OR=2.00, P<0.05). Individuals exhibiting low GRS, low MEHHP levels, and adhering to healthy lifestyles were associated with the least probability of experiencing high SBP-SD (OR=0.31, P<0.05). Increased PAEs exposure could elevate childhood systolic VVV, and exacerbated the adverse impact of pubertal-related genetic susceptibility on the high VVV of SBP; however, healthy lifestyles might alleviate these adverse effects. Promoting healthy lifestyles and reducing PAEs exposure for preventing elevated BP variability among children is important, especially for individuals with greater genetic susceptibility to early pubertal onset. ENVIRONMENTAL IMPLICATION: Blood pressure (BP) in children can vary, as a noninvasive, inexpensive and applicable method, the extent of visit-to-visit variability (VVV) is at least partially independent of BP. The interactions between phthalates (PAEs) exposure, variants of puberty-related genes and lifestyles on VVV are not investigated. Increased childhood systolic VVV might be associated with PAEs exposure, with the associations more pronounced combined with pubertal genetic susceptibility. Yet, healthy habits could partly eliminate such adverse effects. Our study underscores the importance of advocating for healthy lifestyles and reducing exposure to PAEs, especially among individuals with high genetic susceptibility to early puberty onset.

Both hormones and energy-rich compounds play a role in the mitigation of elevated pH on aluminum toxicity in Citrus sinensis leaves.

The contribution of plant hormones and energy-rich compounds and their metabolites (ECMs) in alleviating aluminum (Al) toxicity by elevated pH remains to be clarified. For the first time, a targeted metabolome was applied to identify Al-pH-interaction-responsive hormones and ECMs in Citrus sinensis leaves. More Al-toxicity-responsive hormones and ECMs were identified at pH 4.0 [4 (10) upregulated and 7 (17) downregulated hormones (ECMs)] than those at pH 3.0 [1 (9) upregulated and 4 (14) downregulated hormones (ECMs)], suggesting that the elevated pH improved the adaptation of hormones and ECMs to Al toxicity in leaves. The roles of hormones and ECMs in reducing leaf Al toxicity mediated by elevated pH might include the following aspects: (a) improved leaf growth by upregulating the levels of jasmonoyl-L-isoleucine (JA-ILE), 6-benzyladenosine (BAPR), N6-isopentenyladenosine (IPR), cis-zeatin-O-glucoside riboside (cZROG), and auxins (AUXs), preventing Al toxicity-induced reduction of gibberellin (GA) biosynthesis, and avoiding jasmonic acid (JA)-mediated defense; (b) enhanced biosynthesis and accumulation of tryptophan (TRP), as well as the resulting increase in biosynthesis of auxin, melatonin and secondary metabolites (SMs); (c) improved ability to maintain the homeostasis of ATP and other phosphorus (P)-containing ECMs; and (d) enhanced internal detoxification of Al due to increased organic acid (OA) and SM accumulation and elevated ability to detoxify reactive oxygen species (ROS) due to enhanced SM accumulation. To conclude, the current results corroborate the hypotheses that elevated pH reduces Al toxicity by upregulating the ability to maintain the homeostasis of ATP and other P-containing ECMs in leaves under Al toxicity and (b) hormones participate in the elevated pH-mediated alleviation of Al toxicity by positively regulating growth, the ability to detoxify ROS, and the internal detoxification of Al in leaves under Al toxicity. Our findings provide novel insights into the roles of hormones and ECMs in mitigating Al toxicity mediated by the elevated pH.

Reflectance spectroscopy analysis and lithium content estimation in lithium-rich rocks and stream sediments: Insights from Tuanjie Peak, Western Kunlun, China.

Lithium, a rare metal of strategic importance, has garnered heightened global attention. This investigation delves into the laboratory visible-near infrared and short-wavelength infrared reflectance (VNIR-SWIR 350 nm-2500 nm) spectral properties of lithium-rich rocks and stream sediments, aiming to elucidate their quantitative relationship with lithium concentration. This research seeks to pave new avenues and furnish innovative technical solutions for probing sedimentary lithium reserves. Conducted in the Tuanjie Peak region of Western Kunlun, Xinjiang, China, this study analyzed 614 stream sediments and 222 rock specimens. Initial steps included laboratory VNIR-SWIR spectral reflectance measurements and lithium quantification. Following the preprocessing of spectral data via Savitzky-Golay (SG) smoothing and continuum removal (CR), the absorption positions (Pos2210nm, Pos1910nm) and depths (Depth2210, Depth1910) in the rock spectra, as well as the Illite Spectral Maturity (ISM) of the rock samples, were extracted. Employing both the Successive Projections Algorithm (SPA) and genetic algorithm (GA), wavelengths indicative of lithium content were identified. Integrating the lithium-sensitive wavelengths identified by these feature selection methods, A quantitative predictive regression model for lithium content in rock and stream sediments was developed using partial least squares regression (PLSR), support vector regression (SVR), and convolutional neural network (CNN). Spectral analysis indicated that lithium is predominantly found in montmorillonite and illite, with its content positively correlating with the spectral maturity of illite and closely related to Al-OH absorption depth (Depth2210) and clay content. The SPA algorithm was more effective than GA in extracting lithium-sensitive bands. The optimal regression model for quantitative prediction of lithium content in rock samples was SG-SPA-CNN, with a correlation coefficient prediction (Rp) of 0.924 and root-mean-square error prediction (RMSEP) of 0.112. The optimal model for the prediction of lithium content in stream sediment was SG-SPA-CNN, with an Rp and RMSEP of 0.881 and 0.296, respectively. The higher prediction accuracy for lithium content in rocks compared to sediments indicates that rocks are a more suitable medium for predicting lithium content. Compared to the PLSR and SVR models, the CNN model performs better in both sample types. Despite the limitations, this study highlights the effectiveness of hyperspectral technology in exploring the potential of clay-type lithium resources in the Tuanjie Peak area, offering new perspectives and approaches for further exploration.