Synergistic effect of silicon availability and salinity on metal adsorption in a common estuarine diatom.

Increasing nitrogen and phosphorus discharge and decreasing sediment input have made silicon (Si) a limiting element for diatoms in estuaries. Disturbances in nutrient structure and salinity fluctuation can greatly affect metal uptake by estuarine diatoms. However, the combined effects of Si and salinity on metal accumulation in these diatoms have not been evaluated. In this study, we aimed to investigate how salinity and Si availability combine to influence the adsorption of metals by a widely distributed diatom Phaeodactylum tricornutum. Our data indicate that replete Si and low salinity in seawater can enhance cadmium and copper adsorption onto the diatom surface. At the single-cell level, surface potential was a dominant factor determining metal adsorption, while surface roughness also contributed to the higher metal loading capacity at lower salinities. Using a combination of non-invasive micro-test technology, atomic force microscopy, X-ray photoelectron spectroscopy, and Fourier transform infrared spectroscopy, we demonstrate that the diversity and abundance of the functional groups embedded in diatom cell walls vary with salinity and Si supply. This results in a change in the cell surface potential and transient metal influx. Our study provides novel mechanisms to explain the highly variable metal adsorption capacity of a model estuarine diatom.

Newborn concurrent hearing and genetic screening for hearing impairment: A systematic review and meta­analysis.

Hearing loss is the most prevalent neurosensory disorder in humans, with significant implications for language, social and cognitive development if not diagnosed and treated early. The present systematic review and meta-analysis aimed to determine the rate of hearing screening pass and genetic screening failure [universal newborn hearing screening (UNHS) pass/genetic failure] and to investigate the advantages of combining newborn hearing and genetic screening for newborn hearing impairment. The PubMed, Embase and Cochrane databases were searched from inception to September 2023 to identify studies reporting the combination of neonatal hearing screening with genetic screening. Duplicate literature, unpublished literature, studies with incomplete data, animal experiments, literature reviews and systematic studies were excluded. All the data were processed by STATA15.1 statistical software. A total of nine cross-sectional studies were included in this meta-analysis. The sample sizes ranged from 1,716 to 180,469, and there were a total of 377,688 participants. The pooled results revealed that the prevalence of passing the UNHS while failing genetic screening was 0.31% (95% CI, 0.22-0.41%). The prevalence of UNHS pass and gap junction protein beta 2 and solute carrier family 26 member 4 variant screen failure was 0.01% (95% CI, 0.00-0.02%) and 0.00% (95% CI, 0.00%), respectively, while the prevalence of mitochondrially encoded 12S RRNA variant screening failure and UNHS pass was 0.21% (95% CI, 0.18-0.26%). Combined screening has a significant advantage over pure hearing screening, especially in terms of identifying newborns with mitochondrial gene mutations that render them sensitive to certain medications. In clinical practice, decision-makers can consider practical circumstances and leverage the benefits of combined newborn hearing and genetic screening for early diagnosis, early counseling, and early intervention in patients with hearing loss.

CCL5/CCR5/CYP1A1 pathway prompts liver cancer cells to survive in the combination of targeted and immunological therapies.

Combination therapy of anti-programmed cell death protein-1 (PD-1) antibodies and tyrosine kinase inhibitors (TKIs) has significantly improved the prognosis for hepatocellular carcinoma (HCC), but many patients still have unsatisfactory outcomes. CD8 T cells are known to exert a pivotal function in the immune response against tumors. Nevertheless, most CD8 T cells in HCC tissues are in a state of exhaustion, losing the cytotoxic activity against malignant cells. Cytokines, mainly secreted by immune cells, play an important role in the occurrence and development of tumors. Here, we demonstrated the changes in exhausted CD8T cells during combination therapy by single-cell RNA sequencing (scRNA-seq) analysis on tumor samples before and after treatment. Combination therapy exerted a substantial impact on the exhausted CD8T cells, particularly in terms of cytokine expression. CCL5 was the most abundantly expressed cytokine in CD8T cells and exhausted CD8T cells, and its expression increased further after treatment. Subsequently, we discovered the CCL5/CCR5/CYP1A1 pathway through RNA sequencing (RNA-seq) on CCL5-stimulated Huh7 cells and verified through a series of experiments that this pathway can mediate the resistance of liver cancer cells to lenvatinib. Tissue experiments showed that after combination therapy, the CCL5/CCR5/CYP1A1 pathway was activated, which can benefit the residual tumor cells to survive treatment. Tumor-bearing mouse experiments demonstrated that bergamottin (BGM), a competitive inhibitor of CYP1A1, can enhance the efficacy of both lenvatinib and combination therapy. Our research revealed one mechanism by which hepatoma cells can survive the combination therapy, providing a theoretical basis for the refined treatment of HCC.

A Brief Review of Effects of Aluminum on Marine Diatoms.

Aluminum (Al) is the most abundant metal element in the Earth's crust, yet it is present in trace levels in seawater. Growing evidence suggests potential effects of Al on the biogeochemical cycles of carbon (C) and silicon (Si) in the marine environment. By accumulation, sinking, and deposition, diatoms play a center role in coupling these three elements' biocycles in the oceans. However, it is still a challenge to elucidate the behaviors of diatoms influenced by Al. Our review aims to present the current knowledge of Al biogeochemistry in marine environment and its impact on marine phytoplankton, with a focus on how Al influences diatoms. Previous researches indicate that Al can promote the growth of diatoms, and diatoms have the ability to incorporate Al into their frustules. Given this, we paid particular attention on the interaction between Al and diatom frustules, and the influences of Al on the physiology and ecology of diatoms. Furthermore, it is suggested that Al alters the accumulation of other nutrients such as nitrogen, phosphorus and iron in diatoms; the subsequent responses of diatoms are also discussed. The objective of this review is to address the potential roles of Al in diatoms and offer insights into the possible biogeochemistry implications.

Perovskite Probe-Based Machine Learning Imaging Model for Rapid Pathologic Diagnosis of Cancers.

Accurately distinguishing tumor cells from normal cells is a key issue in tumor diagnosis, evaluation, and treatment. Fluorescence-based immunohistochemistry as the standard method faces the inherent challenges of the heterogeneity of tumor cells and the lack of big data analysis of probing images. Here, we have demonstrated a machine learning-driven imaging method for rapid pathological diagnosis of five types of cancers (breast, colon, liver, lung, and stomach) using a perovskite nanocrystal probe. After conducting the bioanalysis of survivin expression in five different cancers, high-efficiency perovskite nanocrystal probes modified with the survivin antibody can recognize the cancer tissue section at the single cell level. The tumor to normal (T/N) ratio is 10.3-fold higher than that of a conventional fluorescent probe, which can successfully differentiate between tumors and adjacent normal tissues within 10 min. The features of the fluorescence intensity and pathological texture morphology have been extracted and analyzed from 1000 fluorescence images by machine learning. The final integrated decision model makes the area under the receiver operating characteristic curve (area under the curve) value of machine learning classification of breast, colon, liver, lung, and stomach above 90% while predicting the tumor organ of 92% of positive patients. This method demonstrates a high T/N ratio probe in the precise diagnosis of multiple cancers, which will be good for improving the accuracy of surgical resection and reducing cancer mortality.

CCKBR+ cancer cells contribute to the intratumor heterogeneity of gastric cancer and confer sensitivity to FOXO inhibition.

The existence of heterogeneity has plunged cancer treatment into a challenging dilemma. We profiled malignant epithelial cells from 5 gastric adenocarcinoma patients through single-cell sequencing (scRNA-seq) analysis, demonstrating the heterogeneity of gastric adenocarcinoma (GA), and identified the CCKBR+ stem cell-like cancer cells associated poorly differentiated and worse prognosis. We further conducted targeted analysis using single-cell transcriptome libraries, including 40 samples, to confirm these screening results. In addition, we revealed that FOXOs are involved in the progression and development of CCKBR+ gastric adenocarcinoma. Inhibited the expression of FOXOs and disrupting cancer cell stemness reduce the CCKBR+ GA organoid formation and impede tumor progression. Mechanically, CUT&Tag sequencing and Lectin pulldown revealed that FOXOs can activate ST3GAL3/4/5 as well as ST6GALNAC6, promoting elevated sialyation levels in CCKBR+ tumor cells. This FOXO-sialyltransferase axis contributes to the maintenance of homeostasis and the growth of CCKBR+ tumor cells. This insight provides novel perspectives for developing targeted therapeutic strategies aimed at the treating CCKBR associated gastric cancer.

OD-MVSNet: Omni-dimensional dynamic multi-view stereo network.

Multi-view stereo based on learning is a critical task in three-dimensional reconstruction, enabling the effective inference of depth maps and the reconstruction of fine-grained scene geometry. However, the results obtained by current popular 3D reconstruction methods are not precise, and achieving high-accuracy scene reconstruction remains challenging due to the pervasive impact of feature extraction and the poor correlation between cost and volume. In addressing these issues, we propose a cascade deep residual inference network to enhance the efficiency and accuracy of multi-view stereo depth estimation. This approach builds a cost-volume pyramid from coarse to fine, generating a lightweight, compact network to improve reconstruction results. Specifically, we introduce the omni-dimensional dynamic atrous spatial pyramid pooling (OSPP), a multiscale feature extraction module capable of generating dense feature maps with multiscale contextual information. The feature maps encoded by the OSPP module can generate dense point clouds without consuming significant memory. Furthermore, to alleviate the issue of feature mismatch in cost volume regularization, we propose a normalization-based 3D attention module. The 3D attention module aggregates crucial information within the cost volume across the dimensions of channel, spatial, and depth. Through extensive experiments on benchmark datasets, notably DTU, we found that the OD-MVSNet model outperforms the baseline model by approximately 1.4% in accuracy loss, 0.9% in completeness loss, and 1.2% in overall loss, demonstrating the effectiveness of our module.

Leverage Effective Deep Learning Searching Method for Forensic Age Estimation.

Dental age estimation is extensively employed in forensic medicine practice. However, the accuracy of conventional methods fails to satisfy the need for precision, particularly when estimating the age of adults. Herein, we propose an approach for age estimation utilizing orthopantomograms (OPGs). We propose a new dental dataset comprising OPGs of 27,957 individuals (16,383 females and 11,574 males), covering an age range from newborn to 93 years. The age annotations were meticulously verified using ID card details. Considering the distinct nature of dental data, we analyzed various neural network components to accurately estimate age, such as optimal network depth, convolution kernel size, multi-branch architecture, and early layer feature reuse. Building upon the exploration of distinctive characteristics, we further employed the widely recognized method to identify models for dental age prediction. Consequently, we discovered two sets of models: one exhibiting superior performance, and the other being lightweight. The proposed approaches, namely AGENet and AGE-SPOS, demonstrated remarkable superiority and effectiveness in our experimental results. The proposed models, AGENet and AGE-SPOS, showed exceptional effectiveness in our experiments. AGENet outperformed other CNN models significantly by achieving outstanding results. Compared to Inception-v4, with the mean absolute error (MAE) of 1.70 and 20.46 B FLOPs, our AGENet reduced the FLOPs by 2.7×. The lightweight model, AGE-SPOS, achieved an MAE of 1.80 years with only 0.95 B FLOPs, surpassing MobileNetV2 by 0.18 years while utilizing fewer computational operations. In summary, we employed an effective DNN searching method for forensic age estimation, and our methodology and findings hold significant implications for age estimation with oral imaging.

[An in vitro experiment on the stability and irritant of hypochlorous acid in oral cavity].

PURPOSE: To study the stability of physicochemical properties and sterilizing effect about two commercially available hypochlorous acid (HClO) products under simulated clinical conditions, and to evaluate the compatibility of HClO on soft and hard tissues and cells in oral cavity. METHODS: Samples of HClO solution with different production processes were prepared, to detect the changes of physicochemical indexes of each sample over time under simulated clinical conditions (shielded from light at 20-25 ℃, open the cover for 5 minutes every day), including free available chlorine, oxidation-reduction potential and pH. Through suspension quantitative germicidal test, the antibiosis-concentration curve of HClO solution was made, so as to calibrate the change of antibacterial ability of disinfectant with the decrease of available chlorine content during storage. Pulp, tongue and dentine were immersed in PBS, 100 ppm HClO, 200 ppm HClO and 3% NaClO. The influence on soft and hard tissues was evaluated by weighing method and microhardness test. The toxic effects of HClO, NaClO and their 10-fold diluent on human gingival fibroblasts were determined by CCK-8 cytotoxicity assay. GraphPad PRIS 8.0 software was used to analyze the data. RESULTS: Under simulated conditions, the free available chlorine (FAC) of HClO solution decayed with time, and the attenuation degree was less than 20 ppm within 1 month. The bactericidal effect of each HClO sample was still higher than 5log after concentration decay. There was no obvious dissolution and destruction to soft and hard tissues for HClO(P＞0.05). The cell viability of HClO to human gingival fibroblast cells (HGFC) was greater than 80%, which was much higher than 3% NaClO (P＜0.001). CONCLUSIONS: The bactericidal effect and stability of HClO solution can meet clinical needs, which has low cytotoxicity and good histocompatibility. It is expected to become a safe and efficient disinfection product in the field of living pulp preservation and dental pulp regeneration.

Correlation analysis of secondary metabolites and disease resistance activity of different varieties of Congou black tea based on LC-MS/MS and TCMSP.

To investigate the correlation between the difference of secondary metabolites and the disease-resistance activity of different varieties of Congou black tea. Among a total of 657 secondary metabolites identified, 183 metabolites had anti-disease activity, 113 were key active ingredients in traditional Chinese medicine (TCM), 73.22% had multiple anti-disease activities, and all were mainly flavonoids and phenolic acids. The main enriched metabolic pathways were phenylpropanoid biosynthesis, biosynthesis of secondary metabolites, flavonoid biosynthesis, and metabolic pathways. Flavonoid and phenolic acid secondary metabolites were more correlated with anti-disease activity and key active TCM ingredients. Conclusion: The types of JGY and Q601 Congou black tea of the relative contents show large differences in secondary metabolites. Flavonoid and phenolic acid secondary metabolites were identified as the primary factors contributing to the variation in secondary metabolites among different varieties of Congou black tea. These compounds also exhibited a stronger correlation with disease resistance activity.

Simultaneous Determination of Four Catechins in Black Tea via NIR Spectroscopy and Feature Wavelength Selection: A Novel Approach.

As a non-destructive, fast, and cost-effective technique, near-infrared (NIR) spectroscopy has been widely used to determine the content of bioactive components in tea. However, due to the similar chemical structures of various catechins in black tea, the NIR spectra of black tea severely overlap in certain bands, causing nonlinear relationships and reducing analytical accuracy. In addition, the number of NIR spectral wavelengths is much larger than that of the modeled samples, and the small-sample learning problem is rather typical. These issues make the use of NIRS to simultaneously determine black tea catechins challenging. To address the above problems, this study innovatively proposed a wavelength selection algorithm based on feature interval combination sensitivity segmentation (FIC-SS). This algorithm extracts wavelengths at both coarse-grained and fine-grained levels, achieving higher accuracy and stability in feature wavelength extraction. On this basis, the study built four simultaneous prediction models for catechins based on extreme learning machines (ELMs), utilizing their powerful nonlinear learning ability and simple model structure to achieve simultaneous and accurate prediction of catechins. The experimental results showed that for the full spectrum, the ELM model has better prediction performance than the partial least squares model for epicatechin (EC), epicatechin gallate (ECG), epigallocatechin (EGC), and epigallocatechin gallate (EGCG). For the feature wavelengths, our proposed FIC-SS-ELM model enjoys higher prediction performance than ELM models based on other wavelength selection algorithms; it can simultaneously and accurately predict the content of EC (Rp2 = 0.91, RMSEP = 0.019), ECG (Rp2 = 0.96, RMSEP = 0.11), EGC (Rp2 = 0.97, RMSEP = 0.15), and EGCG (Rp2 = 0.97, RMSEP = 0.35) in black tea. The results of this study provide a new method for the quantitative determination of the bioactive components of black tea.

Phytochemical Research and Anti-Inflammatory Activities of the Ethanol Extract from Anoectochilus Roxburghii (Wall.) Lindl.

Anoectochilus roxburghii is a well-known and valuable traditional Chinese herb due to various medicinal and functional benefits. In-depth investigation is necessary to discover active ingredients and expand its application. In this study, four new compounds (1-4) along with ten known compounds (5-14) were isolated from the ethanol extract of A.roxburghii. Their structures were elucidated by spectroscopic data interpretation. The isolates were screened for their inhibitory activities on the production of NO in lipopolysaccharide (LPS)-stimulated RAW 264.7 macrophages. Among them, compounds 5, 6, 9, 10, 12, 13 and 14 exhibited significant anti-inflammatory activity through inhibiting the release of NO.

Dopamine ß-hydroxylase shapes intestinal inflammation through modulating T cell activation.

BACKGROUND: Inflammatory bowel disease (IBD) is a chronic and relapsing disease characterized by immune-mediated dysfunction of intestinal homeostasis. Alteration of the enteric nervous system and the subsequent neuro-immune interaction are thought to contribute to the initiation and progression of IBD. However, the role of dopamine beta-hydroxylase (DBH), an enzyme converting dopamine into norepinephrine, in modulating intestinal inflammation is not well defined. METHODS: CD4+CD45RBhighT cell adoptive transfer, and 2,4-dinitrobenzene sulfonic acid (DNBS) or dextran sodium sulfate (DSS)-induced colitis were collectively conducted to uncover the effects of DBH inhibition by nepicastat, a DBH inhibitor, in mucosal ulceration, disease severity, and T cell function. RESULTS: Inhibition of DBH by nepicastat triggered therapeutic effects on T cell adoptive transfer induced chronic mouse colitis model, which was consistent with the gene expression of DBH in multiple cell populations including T cells. Furthermore, DBH inhibition dramatically ameliorated the disease activity and colon shortening in chemically induced acute and chronic IBD models, as evidenced by morphological and histological examinations. The reshaped systemic inflammatory status was largely associated with decreased pro-inflammatory mediators, such as TNF-α, IL-6 and IFN-γ in plasma and re-balanced Th1, Th17 and Tregs in mesenteric lymph nodes (MLNs) upon colitis progression. Additionally, the conversion from dopamine (DA) to norepinephrine (NE) was inhibited resulting in increase in DA level and decrease in NE level and DA/NE showed immune-modulatory effects on the activation of immune cells. CONCLUSION: Modulation of neurotransmitter levels via inhibition of DBH exerted protective effects on progression of murine colitis by modulating the neuro-immune axis. These findings suggested a promising new therapeutic strategy for attenuating intestinal inflammation.

Radiomics-Based Prediction of Microvascular Invasion Grade in Nodular Hepatocellular Carcinoma Using Contrast-Enhanced Magnetic Resonance Imaging.

Objective: The aim of this study is to develop and verify a magnetic resonance imaging (MRI)-based radiomics model for predicting the microvascular invasion grade (MVI) before surgery in individuals diagnosed with nodular hepatocellular carcinoma (HCC). Methods: A total of 198 patients were included in the study and were randomly stratified into two groups: a training group consisting of 139 patients and a test group comprising 59 patients. The tumor lesion was manually segmented on the largest cross-sectional slice using ITK SNAP, with agreement reached between two radiologists. The selection of radiomics features was carried out using the LASSO (Least Absolute Shrinkage and Selection Operator) algorithm. Radiomics models were then developed through maximum correlation, minimum redundancy, and logistic regression analyses. The performance of the models in predicting MVI grade was assessed using the area under the receiver operating characteristic curve (AUC) and metrics derived from the confusion matrix. Results: There were no notable statistical differences in sex, age, BMI (body mass index), tumor size, and location between the training and test groups. The AP and PP radiomic model constructed for predicting MVI grade demonstrated an AUC of 0.83 (0.75-0.88) and 0.73 (0.64-0.80) in the training group and an AUC of 0.74 (0.61-0.85) and 0.62 (0.48-0.74) in test group, respectively. The combined model consists of imaging data and clinical data (age and AFP), achieved an AUC of 0.85 (0.78-0.91) and 0.77 (0.64-0.87) in the training and test groups, respectively. Conclusion: A radiomics model utilizing-contrast-enhanced MRI demonstrates strong predictive capability for differentiating MVI grades in individuals with nodular HCC. This model could potentially function as a dependable and resilient tool to support hepatologists and radiologists in their preoperative decision-making processes.

Elevated lead mobility in sediments of a eutrophic drinking water reservoir during spring and summer seasons: Insights from isotopic signatures.

Lead (Pb) pollution in sediments remains a major concern for ecosystem quality due to the robust interaction at the sediment/water interface, particularly in shallow lakes. However, understanding the mechanism behind seasonal fluctuations in Pb mobility in these sediments is lacking. Here, the seasonal variability of Pb concentration and isotopic ratio were investigated in the uppermost sediments of a shallow eutrophic drinking lake located in southeast China. Results reveal a sharp increase in labile Pb concentration during autumn-winter period, reaching ∼ 3-fold higher levels than during the spring-summer seasons. Despite these fluctuations, there was a notable overlap in the Pb isotopic signatures within the labile fraction across four seasons, suggesting that anthropogenic sources are not responsible for the elevated labile Pb concentration in autumn-winter seasons. Instead, the abnormally elevated labile Pb concentration during autumn-winter was probably related to reduction dissolution of Fe/Mn oxides, while declined labile Pb concentration during spring-summer may be attributed to adsorption/precipitation of Fe/Mn oxides. These large seasonal changes imply the importance of considering seasonal effects when conducting sediment sampling. We further propose a solution that using Pb isotopic signatures within the labile fraction instead of the bulk sediment can better reflect the information of anthropogenic Pb sources.

Lactate drives epithelial-mesenchymal transition in diabetic kidney disease via the H3K14la/KLF5 pathway.

High levels of urinary lactate are an increased risk of progression in patients with diabetic kidney disease (DKD). However, it is still unveiled how lactate drive DKD. Epithelial-mesenchymal transition (EMT), which is characterized by the loss of epithelial cells polarity and cell-cell adhesion, and the acquisition of mesenchymal-like phenotypes, is widely recognized a critical contributor to DKD. Here, we found a switch from oxidative phosphorylation (OXPHOS) toward glycolysis in AGEs-induced renal tubular epithelial cells, thus leading to elevated levels of renal lactic acid. We demonstrated that reducing the lactate levels markedly delayed EMT progression and improved renal tubular fibrosis in DKD. Mechanically, we observed lactate increased the levels of histone H3 lysine 14 lactylation (H3K14la) in DKD. ChIP-seq & RNA-seq results showed histone lactylation contributed to EMT process by facilitating KLF5 expression. Moreover, KLF5 recognized the promotor of cdh1 and inhibited its transcription, which accelerated EMT of DKD. Additionally, nephro-specific knockdown and pharmacological inhibition of KLF5 diminished EMT development and attenuated DKD fibrosis. Thus, our study provides better understanding of epigenetic regulation of DKD pathogenesis, and new therapeutic strategy for DKD by disruption of the lactate-drived H3K14la/KLF5 pathway.

New alkaloids from Stemona tuberosa and structural revision of tuberostemonols P and R.

Three Stemona alkaloids named stemotuberines A-C (1-3) with unique C17N frameworks, presumably formed by elimination of the C-11-C-15 lactone ring of the stichoneurine skeleton, were isolated from the roots of Stemona tuberosa. Their structures were elucidated by spectroscopic analysis, X-ray diffraction, and computational methods. Compounds 2 and 3 showed inhibition (IC50 values of 37.1 and 23.2 µM, respectively) against LPS-induced nitric oxide production in RAW 264.7 cells. In addition, concern was expressed about the reported plant origin (S. sessilifolia) of the recently described alkaloids tuberostemonols O-R (4-7), which should be S. tuberosa. NMR calculations indicated structural misassignment of these compounds except for 6. Isolation of tuberostemonol P (5) from our material of S. tuberosa allowed for a close examination of the spectroscopic data leading to the revised structure 5a. Tuberostemonol R (7) was found to have identical 1H and 13C NMR data to the well-known alkaloid croomine, and therefore its structure including relative stereochemistry must be revised as 7a.

Long-term water demand forecasting using artificial intelligence models in the Tuojiang River basin, China.

Accurate forecasts of water demand are a crucial factor in the strategic planning and judicious use of finite water resources within a region, underpinning sustainable socio-economic development. This study aims to compare the applicability of various artificial intelligence models for long-term water demand forecasting across different water use sectors. We utilized the Tuojiang River basin in Sichuan Province as our case study, comparing the performance of five artificial intelligence models: Genetic Algorithm optimized Back Propagation Neural Network (GA-BP), Extreme Learning Machine (ELM), Gaussian Process Regression (GPR), Support Vector Regression (SVR), and Random Forest (RF). These models were employed to predict water demand in the agricultural, industrial, domestic, and ecological sectors using actual water demand data and relevant influential factors from 2005 to 2020. Model performance was evaluated based on the Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE), with the most effective model used for 2025 water demand projections for each sector within the study area. Our findings reveal that the GPR model demonstrated superior results in predicting water demand for the agricultural, domestic, and ecological sectors, attaining R2 values of 0.9811, 0.9338, and 0.9142 for the respective test sets. Also, the GA-BP model performed optimally in predicting industrial water demand, with an R2 of 0.8580. The identified optimal prediction model provides a useful tool for future long-term water demand forecasting, promoting sustainable water resource management.

Predictive value of fluorometric method and tandem mass spectrometry for hyperphenylalaninemia and its subtypes in China: A systematic review and meta­analysis.

The present study aimed to conduct a comprehensive meta-analysis to assess the diagnostic value of fluorometric assays and tandem mass spectrometry (MS/MS) for hyperphenylalaninemia (HPA) and its subtypes. The PubMed, Embase and Cochrane Library databases were searched from inception to October 2023. The present study included studies that reported the newborn screening and genetic features of patients with HPA and excluded duplicate publications, studies without full text, studies with incomplete information, studies from which it was not possible to extract data, animal experiments, reviews and systematic reviews. STATA 15.1 was used to analyze the data. The pooled results revealed that 0.04% [95% confidence interval (CI): 0.019-0.069] of neonatal HPA fluorometric assays and MS/MS. The positive predictive value (PPV) of neonatal HPA screening using fluorometric assays and tandem mass spectrometry was 31.7% (95% CI: 19.6-45.2). Notably, the PPV of neonatal HPA screening using fluorometric assays was 8.3% (95% CI: 7.1-9.6), while the PPV of neonatal HPA screening using tandem mass spectrometry was 31.8% (95% CI: 16.4-49.4). Additionally, the pooled results showed that the incidence of tetrahydrobiopterin deficiency (BH4D) in HPA patients was 12.43% (95% CI: 3.28-25.75) and the incidence of phenylalanine hydroxylase deficiency (PAHD) in HPA patients was 88.65% (95% CI: 78.84-95.86). Newborn screening is an effective method for the early detection of HPA and MS/MS has a greater PPA than fluorometric assays for diagnosing HPA. In addition, in the screening of HPA, the proportion of HPA patients with PAHD was significantly higher than that of patients with BH4D.

Intraoperative intensive blood pressure management strategy and the outcome of patients who had an acute ischaemic stroke undergoing endovascular treatment under general anaesthesia: study protocol for a prospective randomised controlled trial.

BackgroundEndovascular thrombectomy is the recommended treatment for acute ischaemic stroke, but the optimal blood pressure management strategy during the procedure under general anaesthesia remains controversial. In this study protocol, we propose an intraoperative intensive blood pressure range (110-140 mm Hg systolic blood pressure) based on a retrospective analysis and extensive literature review. By comparing the outcomes of patients who had an acute ischaemic stroke undergoing mechanical thrombectomy under general anaesthesia with standard blood pressure management (140-180 mm Hg systolic blood pressure) versus intensive blood pressure management, we aim to determine the impact of intraoperative intensive blood pressure management strategy on patient prognosis. METHODS AND ANALYSIS: The study is a double-blinded, randomised, controlled study, with patients randomised into either the standard blood pressure management group or the intensive blood pressure management group. The primary endpoint of the study will be the sequential analysis of modified Rankin Scale scores at 90 days after mechanical thrombectomy. ETHICS AND DISSEMINATION: The study has been approved by the ethics committee of Shanghai Changhai Hospital with an approval number CHEC2023-015. The results of the study will be published in peer-reviewed international journals. TRIAL REGISTRATION NUMBER: ChiCTR2300070764.