Hepatic portal venous gas after ingesting glyphosate: A case report and literature review.

Background: Glyphosate is a widely used herbicide. Clinical presentations of glyphosate intoxication show variation, but hepatic portal venous gas(HPVG) caused by glyphosate poisoning is rarely reported. Herein, we report a rare case of ominous HPVG after ingesting glyphosate. HPVG, which used to be an ominous abdominal radiologic sign, is associated with numerous underlying abdominal pathologies, ranging from benign conditions that require no invasive treatment to potentially lethal diseases that necessitate prompt surgical intervention. Case summary: A young woman who ingested 100 mL glyphosate 6-h prior was admitted to the emergency intensive care unit. Before admission to our hospital, the patient was administered gastric lavage treatment with 10000 mL of normal saline in the local hospital. After 14 h, her laboratory examinations showed systemic inflammatory response syndrome and multiple organ dysfunction syndrome, while the condition deteriorated. Computed tomography of the abdomen showed multilinear air densities in the portal vein, hepatic branches, and mesenteric vessels, intestinal obstruction, and intestinal necrosis. Septic shock and a severe abdominal infection were diagnosed. The patient was treated conservatively as they could not tolerate surgery and, after 20 h died of septic shock. Conclusion: We reviewed 289 cases of "hepatic portal venous gas" in PUBMED and analyzed the etiology and treatment of HPVG accompanied by the underlying pathology. We concluded that HPVG is a radiological sign associated with various diseases, and the prognosis mainly depends on the underlying cause and clinical condition. As glyphosate may erode the digestive tract, attention should be paid to the volume, pressure, and speed of gastric lavage in treating glyphosate poisoning to avoid fatal complications such as HPVG. Abdominal symptoms need to be closely observed, and changes in the early onset of the condition in clinical practice need to be responded to promptly.

Real-world effectiveness of adjuvant octreotide therapy in patients with pancreatic neuroendocrine tumors at high recurrence risk: A multicenter retrospective cohort study.

Adjuvant therapy for pancreatic neuroendocrine tumors (PanNETs) after radical resection lacks evidence-based data and remains controversial. This study aimed to validate whether long-acting octreotide is a potential candidate for adjuvant therapy in patients with G2 PanNETs at high recurrence risk by clustering real-world data. A retrospective review of patients with nonmetastatic grade 2 PanNETs who underwent radical resection at six research centers between 2008 and 2020 was conducted. Propensity score matching and inverse probability of treatment weight analysis were used to control confounding factors. Overall, 357 patients (octreotide group, n = 82; control group, n = 275) were analyzed. Kaplan-Meier survival analyses showed that the octreotide group had longer disease-free survival (DFS) compared with the control group (36 months: 93.3% vs. 79.0%, p = .0124; 60 months: 71% vs. 67.6%, p = .0596, respectively), as well as overall survival (OS) (60 months: 98% vs. 83.8%, p = .0117, respectively). Multivariate analyses indicated that octreotide long-acting repeatable (LAR) adjuvant therapy was associated with higher OS (p = .0270) at 60 months. Propensity score matching analysis showed that octreotide adjuvant therapy was associated with higher DFS (p = .0455) and OS (p = .0190) at 60 months. Similar results were obtained via inverse probability of treatment weight analysis. Subgroup analysis indicated that octreotide LAR was associated with a high DFS in patients with lymph node metastasis or Ki-67 <10% PanNETs. Adjuvant therapy with long-acting octreotide following radical resection of nonmetastatic G2 PanNETs may be associated with improved DFS and OS in a real-world setting.

Congenital myopathies: pathophysiological mechanisms and promising therapies.

Congenital myopathies (CMs) are a kind of non-progressive or slow-progressive muscle diseases caused by genetic mutations, which are currently defined and categorized mainly according to their clinicopathological features. CMs exhibit pleiotropy and genetic heterogeneity. Currently, supportive treatment and pharmacological remission are the mainstay of treatment, with no cure available. Some adeno-associated viruses show promising prospects in the treatment of MTM1 and BIN1-associated myopathies; however, such gene-level therapeutic interventions target only specific mutation types and are not generalizable. Thus, it is particularly crucial to identify the specific causative genes. Here, we outline the pathogenic mechanisms based on the classification of causative genes: excitation-contraction coupling and triadic assembly (RYR1, MTM1, DNM2, BIN1), actin-myosin interaction and production of myofibril forces (NEB, ACTA1, TNNT1, TPM2, TPM3), as well as other biological processes. Furthermore, we provide a comprehensive overview of recent therapeutic advancements and potential treatment modalities of CMs. Despite ongoing research endeavors, targeted strategies and collaboration are imperative to address diagnostic uncertainties and explore potential treatments.

Remifentanil vs. dexmedetomidine for cardiac surgery patients with noninvasive ventilation intolerance: a multicenter randomized controlled trial.

BACKGROUND: The optimal sedative regime for noninvasive ventilation (NIV) intolerance remains uncertain. The present study aimed to assess the efficacy and safety of remifentanil (REM) compared to dexmedetomidine (DEX) in cardiac surgery patients with moderate-to-severe intolerance to NIV. METHODS: In this multicenter, prospective, single-blind, randomized controlled study, adult cardiac surgery patients with moderate-to-severe intolerance to NIV were enrolled and randomly assigned to be treated with either REM or DEX for sedation. The status of NIV intolerance was evaluated using a four-point NIV intolerance score at different timepoints within a 72-h period. The primary outcome was the mitigation rate of NIV intolerance following sedation. RESULTS: A total of 179 patients were enrolled, with 89 assigned to the REM group and 90 to the DEX group. Baseline characteristics were comparable between the two groups, including NIV intolerance score [3, interquartile range (IQR) 3-3 vs. 3, IQR 3-4, p = 0.180]. The chi-squared test showed that mitigation rate, defined as the proportion of patients who were relieved from their initial intolerance status, was not significant at most timepoints, except for the 15-min timepoint (42% vs. 20%, p = 0.002). However, after considering the time factor, generalized estimating equations showed that the difference was statistically significant, and REM outperformed DEX (odds ratio = 3.31, 95% confidence interval: 1.35-8.12, p = 0.009). Adverse effects, which were not reported in the REM group, were encountered by nine patients in the DEX group, with three instances of bradycardia and six cases of severe hypotension. Secondary outcomes, including NIV failure (5.6% vs. 7.8%, p = 0.564), tracheostomy (1.12% vs. 0%, p = 0.313), ICU LOS (7.7 days, IQR 5.8-12 days vs. 7.0 days, IQR 5-10.6 days, p = 0.219), and in-hospital mortality (1.12% vs. 2.22%, p = 0.567), demonstrated comparability between the two groups. CONCLUSIONS: In summary, our study demonstrated no significant difference between REM and DEX in the percentage of patients who achieved mitigation among cardiac surgery patients with moderate-to-severe NIV intolerance. However, after considering the time factor, REM was significantly superior to DEX. Trial registration ClinicalTrials.gov (NCT04734418), registered on January 22, 2021. URL of the trial registry record: https://register. CLINICALTRIALS: gov/prs/app/action/SelectProtocol?sid=S000AM4S&selectaction=Edit&uid=U00038YX&ts=3&cx=eqn1z0 .

Quantified low voltage electrostatic field: The effects of intensity on cherry tomato preservation and mechanism.

Low voltage electrostatic field (LVEF), a novel non-thermal processing technology, shows promise for food preservation. However, the absence of clear definition and quantification of the core concept "low voltage" obstructs the effective application of LVEF. This study assessed the efficiency of various LVEF intensities (100, 200, 300 V) on cherry tomato preservation, revealing significant differences in preservation efficiency. Compared to the control, samples treated with different intensities showed varied reductions in weight loss (6.26-25.45 %), firmness changes (5.17-28.91 %), and decay incidence (47.91-70.89 %). Quantitative analysis elucidated that the differential preservation efficiency may arise from a dose-response relationship between electric field strength and hydrogen peroxide (H2O2) content， identifying an optimal H2O2 content range of 21.18-27.01 mmol kg-1 for the effective preservation of cherry tomatoes under LVEF. These findings highlight the importance of precise LVEF intensity control for effective food preservation and offer insights for developing optimal LVEF treatment intensities for diverse produce.

Virtual birefringence imaging and histological staining of amyloid deposits in label-free tissue using autofluorescence microscopy and deep learning.

Systemic amyloidosis involves the deposition of misfolded proteins in organs/tissues, leading to progressive organ dysfunction and failure. Congo red is the gold-standard chemical stain for visualizing amyloid deposits in tissue, showing birefringence under polarization microscopy. However, Congo red staining is tedious and costly to perform, and prone to false diagnoses due to variations in amyloid amount, staining quality and manual examination of tissue under a polarization microscope. We report virtual birefringence imaging and virtual Congo red staining of label-free human tissue to show that a single neural network can transform autofluorescence images of label-free tissue into brightfield and polarized microscopy images, matching their histochemically stained versions. Blind testing with quantitative metrics and pathologist evaluations on cardiac tissue showed that our virtually stained polarization and brightfield images highlight amyloid patterns in a consistent manner, mitigating challenges due to variations in chemical staining quality and manual imaging processes in the clinical workflow.

Development and external validation of a novel modality for rapid recognition of aortic dissection based on peripheral pulse oximetry waveforms.

BACKGROUND: Aortic dissection (AD) is a life-threatening cardiovascular emergency that is often misdiagnosed as other chest pain conditions. Physiologically, AD may cause abnormalities in peripheral blood flow, which can be detected using pulse oximetry waveforms. PURPOSE: This study aimed to assess the feasibility of identifying AD based on pulse oximetry waveforms and to highlight the key waveform features that play a crucial role in this diagnostic method. METHODS: This prospective study employed high-risk chest pain cohorts from two emergency departments. The initial cohort was enriched with AD patients (n = 258, 47% AD) for model development, while the second cohort consisted of chest pain patients awaiting angiography (n = 71, 25% AD) and was used for external validation. Pulse oximetry waveforms from the four extremities were collected for each patient. After data preprocessing, a recognition model based on the random forest algorithm was trained using patients' gender, age, and waveform difference features extracted from the pulse oximetry waveforms. The performance of the model was evaluated using receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA). The importance of features was also assessed using Shapley Value and Gini importance. RESULTS: The model demonstrated strong performance in identifying AD in both the training and external validation sets. In the training set, the model achieved an area under the ROC curve of 0.979 (95% CI: 0.961-0.990), sensitivity of 0.918 (95% CI: 0.873-0.955), specificity of 0.949 (95% CI: 0.912-0.985), and accuracy of 0.933 (95% CI: 0.904-0.959). In the external validation set, the model attained an area under the ROC curve of 0.855 (95% CI: 0.720-0.965), sensitivity of 0.889 (95% CI: 0.722-1.000), specificity of 0.698 (95% CI: 0.566-0.812), and accuracy of 0.794 (95% CI: 0.672-0.878). Decision curve analysis (DCA) further showed that the model provided a substantial net benefit for identifying AD. The median mean and median variance of the four limbs' signals were the most influential features in the recognition model. CONCLUSIONS: This study demonstrated the feasibility and strong performance of identifying AD based on peripheral pulse oximetry waveforms in high-risk chest pain populations in the emergency setting. The findings also provided valuable insights for future human fluid dynamics simulations to elucidate the impact of AD on blood flow in greater detail.

Nanotechnology-based approaches for antibacterial therapy.

The technique of antimicrobial therapy action is to stop or slow the growth of bacteria that can kill people, animals, and crops. The most widely used antibacterial agents are antibiotics. Even though these antimicrobial medications are quite effective, there are still certain barriers or challenges in using them effectively. To solve these issues, new antimicrobial drug molecules that don't have side effects or resistance are needed. These days, antimicrobial drugs placed in nanosized vehicles, or nanomedicine, made of different metal and metallic oxides as well as of polymer, carbon or lipid-based may be used to address these issues with conventional therapy and delivery techniques. This review focuses on the importance of nanotechnology in antimicrobial therapy, nanoparticles (NPs) used in this therapy, their mode of action, and the recent advancement in nanotechnology for antimicrobial therapy.

Valorization of sewage sludge incineration ash as a novel soilless growing medium for urban agriculture and greenery.

Limited open areas for urban agriculture and greenery have led to the search for innovative, sustainable growing media to strengthen the food supply and improve atmospheric quality for a resilient city. Rampant land developments have caused soil to become increasingly scarce. Sewage sludge incineration ash (SSIA), the by-product of waste-to-energy (WtE) incineration of sewage sludge, is a major municipal waste containing phosphorus-fertilizing nutrients. For the first time, we investigated the novel application of SSIA as a soilless plant-growing medium with built-in fertilizer. SSIA outperformed topsoil in bulk density, water-holding capacity, porosity, and nutrient content. However, it was found that SSIA has a high salinity and should be treated first. Wheatgrass (Triticum aestivum L.), a fast-growing glycophyte, thrived in the desalinated SSIA, showing growth and nutrient content comparable to the topsoil case. Simultaneously, it demonstrated phytoremediation. The SSIA residue was then recycled into cementitious materials, using desalinating water for mixing. SSIA upcycle into a growing medium facilitates urban resource management by utilizing nutrients in sewage waste for eco-friendly plant cultivation, benefiting urban agriculture and greenery. It is also a prudent valorization step before further recycling SSIA to reduce landfill requirements.

Multi-site and long-term estimation of phosphorus dynamics for paddy surface water in China based on new MLEpaddy-P.

Paddy surface water serves as the primary source of artificial drainage and rainfall runoff leading to phosphorus (P) loss from paddy fields. The quantification of P dynamics in paddy surface water on a large scale is challenging due to the spatiotemporal heterogeneity of influencing factors and the limitations of field measurements. Based on 1226 data sets from 33 field sites covering the three main rice-growing regions of China (the Southeast Coast, the Yangtze River Basin, and the Northeast Plain), we analyzed the spatiotemporal characteristics of P attenuation in paddy surface water and its influencing factors. A new multi-site and long-term phosphorus estimation model for paddy (MLEpaddy-P) was proposed to evaluate the total phosphorus (TP) dynamics at national scale by improving the initial concentration (C0) and attenuation coefficient (k) of the first-order kinetic model (Ct=C0∙e-k(t-1)). Our study showed that: (1) Fertilizer amounts, soil organic matter content, soil Olsen-P content, soil pH, and soil total phosphorus are the primary factors affecting the variation of C0 and k; (2) Yangtze River Basin possessed the highest C0 (6.87 ± 12.97 mg/L) and high k ≤ 7 (0.262 in 1-7 days after fertilization), followed by Southeast Coast (4.15 ± 5.33 mg/L; 0.263) and Northeast Plain (1.33 ± 1.50 mg/L; 0.239), respectively; (3) MLEpaddy-P performed well in daily TP dynamics estimation at national scale with R2 of 0.74-0.85; (4) Middle and lower reaches of the Yangtze River Basin were the critical regions with high TP concentration due to high fertilizer amount and soil Olsen-P content. The new universal model realizes the multi-site and long-term estimation of P dynamics while greatly saving multi-site monitoring costs. This study provides a basis for early warning and targeted control of P loss from paddies.

Impact of Type of Lenvatinib Resistance on Prognosis and Second-Line Regimen in Patients with Virus-Associated HCC.

Background: Lenvatinib is the first-line treatment option for patients with advanced hepatocellular carcinoma (HCC); however, the impact of lenvatinib resistance on patient prognosis is unknown. Methods: We recruited all patients with advanced HCC who received first-line lenvatinib treatment between February 2019 and February 2023 at two medical centers in China, according to the selection criteria. The patients were divided into primary and secondary resistance groups based on tumor progression within 3 months. The Kaplan-Meier method was used to calculate progression-free survival (PFS) and overall survival (OS). Logistic regression and Cox proportional hazards models were used to explore factors influencing drug resistance and prognosis. The study end points were drug resistance, PFS, and OS. Results: A total of 531 patients met the study criteria, with 169 (31.8%) and 362 (68.2%) patients in the primary and secondary groups, respectively. An alpha-fetoprotein (AFP) concentration > 400 ng/mL was an independent risk factor for primary drug resistance. Patients in the primary group had a significantly shorter median OS (11.0 vs 31.0 months, P<0.001) than those in the secondary group. The 1-, 2- and 3-year cumulative survival rates in the primary group were 46.3%, 22.2%, and 10.1%, while those in the secondary group were 82.3%, 59.1% and 44.9%, respectively. Compared to tyrosine kinase inhibitor (TKI) monotherapy, longer median PFS (4.0 vs 7.0 months, P=0.008) and OS (11.0 vs 23.0 months, P=0.024) were achieved with the combination of a TKI plus a PD-1 inhibitor as a second-line therapy after lenvatinib resistance. Conclusion: There is a high rate of primary resistance to lenvatinib in patients with HCC and the prognosis for those with primary resistance is poor. TKI combined with PD-1 inhibitors should be preferentially recommended for lenvatinib-resistant patients.

Genome-wide analysis of the NYN domain gene family in Brassica napus and its function role in plant growth and development.

The NYN domain gene family consists of genes that encode ribonucleases that are characterized by a newly identified NYN domain. Members of the family were widely distributed in all life kingdoms and play a crucial role in various RNA regulation processes, although the wide genome overview of the NYN domain gene family is not yet available in any species. Rapeseed (Brassica napus L.), a polyploid model species, is an important oilseed crop. Here, the phylogenetic analysis of these BnaNYNs revealed five distinct groups strongly supported by gene structure, conserved domains, and conserved motifs. The survey of the expansion of the gene family showed that the birth of BnaNYNs is explained by various duplication events. Furthermore, tissue-specific expression analysis, protein-protein interaction prediction, and cis-element prediction suggested a role for BnaNYNs in plant growth and development. Interestingly, the data showed that three tandem duplicated BnaNYNs (TDBs) exhibited distinct expression patterns from those other BnaNYNs and had a high similarity in protein sequence level. Furthermore, the analysis of one of these TDBs, BnaNYN57, showed that overexpression of BnaNYN57 in Arabidopsis thaliana and B. napus accelerated plant growth and significantly increased silique length, while RNA interference resulted in the opposite growth pattern. It suggesting a key role for the TDBs in processes related to plant growth and development.

METTL14 promotes lipid metabolism reprogramming and sustains nasopharyngeal carcinoma progression via enhancing m6A modification of ANKRD22 mRNA.

BACKGROUND: N6-methyladenosine (m6A) modification is essential for modulating RNA processing as well as expression, particularly in the context of malignant tumour progression. However, the exploration of m6A modification in nasopharyngeal carcinoma (NPC) remains very limited. METHODS: RNA m6A levels were analysed in NPC using m6A dot blot assay. The expression level of methyltransferase-like 14 (METTL14) within NPC tissues was analysed from public databases as well as RT-qPCR and immunohistochemistry. The influences on METTL14 expression on NPC proliferation and metastasis were explored via in vitro as well as in vivo functional assays. Targeted genes of METTL14 were screened using the m6A and gene expression profiling microarray data. Actinomycin D treatment and polysome analysis were used to detect the half-life and translational efficiency of ANKRD22. Flow cytometry, immunofluorescence and immunoprecipitation were used to validate the role of ANKRD22 on lipid metabolism in NPC cells. ChIP-qPCR analysis of H3K27AC signalling near the promoters of METTL14, GINS3, POLE2, PLEK2 and FERMT1 genes. RESULTS: We revealed METTL14, in NPC, correlating with poor patient prognosis. In vitro and in vivo assays indicated METTL14 actively promoted NPC cells proliferation and metastasis. METTL14 catalysed m6A modification on ANKRD22 messenger ribonucleic acid (mRNA), recognized by the reader IGF2BP2, leading to increased mRNA stability and higher translational efficiency. Moreover, ANKRD22, a metabolism-related protein on mitochondria, interacted with SLC25A1 to enhance citrate transport, elevating intracellular acetyl-CoA content. This dual impact of ANKRD22 promoted lipid metabolism reprogramming and cellular lipid synthesis while upregulating the expression of genes associated with the cell cycle (GINS3 and POLE2) and the cytoskeleton (PLEK2 and FERMT1) through heightened epigenetic histone acetylation levels in the nucleus. Intriguingly, our findings highlighted elevated ANKRD22-mediated histone H3 lysine 27 acetylation (H3K27AC) signals near the METTL14 promoter, which contributes to a positive feedback loop perpetuating malignant progression in NPC. CONCLUSIONS: The identified METTL14-ANKRD22-SLC25A1 axis emerges as a promising therapeutic target for NPC, and also these molecules may serve as novel diagnostic biomarkers.

Inducing Intermolecular Oxygen Coupling by Introducing S and FeOOH on Co(OH)2 Nanoneedle Arrays for Industrial Water Oxidation.

The design of electrocatalysts for oxygen evolution reaction (OER) remains a limitation of industrial hydrogen production by electrolysis of water. Excellent and stable OER catalysts can be developed by activating lattice oxygen and changing the reaction path. Herein, S and FeOOH on the Co(OH)2 nanoneedle arrays are introduced to construct a heterostructure (S-FeOOH/Co(OH)2/NF) as a proof of concept. Theoretical calculations and experimental suggest that the Co-O-Fe motif formed at the heterogeneous interface with the introduction of FeOOH, inducing electron transfer from Co to Fe, enhancing Co─O covalency and reducing intramolecular charge transfer energy, thereby stimulating direct intramolecular lattice oxygen coupling. Doping of S in FeOOH further accelerates electron transfer, improves lattice oxygen activity, and prevents dissolution of FeOOH. Consequently, the overpotential of S-FeOOH/Co(OH)2/NF is only 199 mV at 10 mA cm-2, and coupled with the Pt/C electrode can be up to 1 A cm-2 under 1.79 V and remain stable for over 120 h in an anion exchange membrane water electrolyzer (AEMWE). This work proposes a strategy for the design of efficient and stable electrocatalysts for industrial water electrolysis and promotes the commercialization of AEMWE.

High-temperature-insensitivity high-power Yb-doped fiber laser directly in-band pumping by 1018 nm laser diodes.

In this Letter, we demonstrate a high-power ytterbium-doped fiber laser (YDFL) based on a directly in-band pumping scheme (DIPS) which employs 1018 nm laser diodes (LDs) as pump sources. The wavelength of the LDs is designed theoretically, considering the distribution of Yb3+ absorption cross section (σa) as well as quantum defect (QD). The flat distribution of σa around 1018 nm ensures excellent temperature insensitivity and flexibility for the YDFL. Besides, lower QD and more compact structure promise higher optical-to-optical (O-O) and electrical-to-optical (E-O) efficiencies. Based on the experimental setup, as the cooling temperature of the 1018 nm LDs ranges from 6 to 23°C, an output power of 2 kW level is achieved that varies by only 2.01% without adjusting the operating current of the LDs subjectively. The output power is then scaled up to 5 kW level. Furthermore, there is a great potential to achieve higher output power and E-O efficiency in YDFLs based on the DIPS.

Construction of Fire Safe Thermoplastic Polyurethane/Reduced Graphene Oxide Hierarchical Composites with Electromagnetic Interference Shielding.

Incorporating outstanding flame retardancy and electromagnetic interference shielding effectiveness (EMI SE) into polymers is a pressing requirement for practical utilization. In this study, we first employed the principles of microencapsulation and electrostatic interaction-driven self-assembly to encapsulate polyethyleneimine (PEI) molecules and Ti3C2Tx nanosheets on the surface of ammonium polyphosphate (APP), forming a double-layer-encapsulated structure of ammonium polyphosphate (APP@PEI@Ti3C2Tx). Subsequently, flame-retardant thermoplastic polyurethane (TPU) composites were fabricated by melting the flame-retardant agent with TPU. Afterwards, by using air-assisted thermocompression technology, we combined a reduced graphene oxide (rGO) film with flame-retardant TPU composites to fabricate hierarchical TPU/APP@PEI@Ti3C2Tx/rGO composites. We systematically studied the combustion behavior, flame retardancy, and smoke-suppression performance of these composite materials, as well as the flame-retardant mechanism of the expansion system. The results indicated a significant improvement in the interface interaction between APP@PEI@Ti3C2Tx and the TPU matrix. Compared to pure TPU, the TPU/10APP@PEI@1TC composite exhibited reductions of 84.1%, 43.2%, 62.4%, and 85.2% in peak heat release rate, total heat release, total smoke release, and total carbon dioxide yield, respectively. The averaged EMI SE of hierarchical TPU/5APP@PEI@1TC/rGO also reached 15.53 dB in the X-band.

Universal high-frequency monitoring methods of river water quality in China based on machine learning.

The in-situ high-frequency monitoring of total nitrogen (TN) and total phosphorus (TP) in rivers is a challenge and key to instant water quality judgment and early warning. Based on the physical and chemical association between TN/TP and sensor-measurable predictors, we proposed a novel "indirect" measurement method for TN and TP in rivers. This method combines the timeliness of multi-sensor and the accuracy of intelligent algorithms, utilizing 188,629 data sets from 131 water monitoring stations across China. Under 5 algorithms and 4 predictor group scenarios, the results showed that: (1) extra tree regression (ETR) with 6 predictors exhibited the best precision, and the mean determination coefficient (R2) of TN and TP inversion across 131 stations reached 0.78 ± 0.25 and 0.79 ± 0.22 respectively; (2) among 6 potential predictors, the importance degrees of temperature, electrical conductivity, NH4-N, and turbidity were greater than that of pH and DO, and >80 % of stations exhibited acceptable prediction accuracy (R2 > 0.6) when the number of predictors (P) ranged from 4 to 6, which showed good tolerability to predictor variations; (3) the accurate classification rates of water quality standard (ACRws) of all stations based on TN and TP reached 90.41 ± 6.96 % and 92.33 ± 6.41 %; (4) in 9 regions/basins of China, this method showed universal application potential with no significant prediction difference. Compared with laboratory test, water quality automatic monitoring station, and remote sensing inversion, the proposed method offers high-frequency, high-precision, regional adaptability, low cost, and stable operation under rainy, cloudy, and nighttime conditions. The new method may provide important technological support for timely pollutant tracing, pre-warning, and emergency control for river pollution.

Structural basis of antagonist selectivity in endothelin receptors.

Endothelins and their receptors, ETA and ETB, play vital roles in maintaining vascular homeostasis. Therapeutically targeting endothelin receptors, particularly through ETA antagonists, has shown efficacy in treating pulmonary arterial hypertension (PAH) and other cardiovascular- and renal-related diseases. Here we present cryo-electron microscopy structures of ETA in complex with two PAH drugs, macitentan and ambrisentan, along with zibotentan, a selective ETA antagonist, respectively. Notably, a specialized anti-ETA antibody facilitated the structural elucidation. These structures, together with the active-state structures of ET-1-bound ETA and ETB, and the agonist BQ3020-bound ETB, in complex with Gq, unveil the molecular basis of agonist/antagonist binding modes in endothelin receptors. Key residues that confer antagonist selectivity to endothelin receptors were identified along with the activation mechanism of ETA. Furthermore, our results suggest that ECL2 in ETA can serve as an epitope for antibody-mediated receptor antagonism. Collectively, these insights establish a robust theoretical framework for the rational design of small-molecule drugs and antibodies with selective activity against endothelin receptors.

Automated HER2 Scoring in Breast Cancer Images Using Deep Learning and Pyramid Sampling.

Objective and Impact Statement: Human epidermal growth factor receptor 2 (HER2) is a critical protein in cancer cell growth that signifies the aggressiveness of breast cancer (BC) and helps predict its prognosis. Here, we introduce a deep learning-based approach utilizing pyramid sampling for the automated classification of HER2 status in immunohistochemically (IHC) stained BC tissue images. Introduction: Accurate assessment of IHC-stained tissue slides for HER2 expression levels is essential for both treatment guidance and understanding of cancer mechanisms. Nevertheless, the traditional workflow of manual examination by board-certified pathologists encounters challenges, including inter- and intra-observer inconsistency and extended turnaround times. Methods: Our deep learning-based method analyzes morphological features at various spatial scales, efficiently managing the computational load and facilitating a detailed examination of cellular and larger-scale tissue-level details. Results: This approach addresses the tissue heterogeneity of HER2 expression by providing a comprehensive view, leading to a blind testing classification accuracy of 84.70%, on a dataset of 523 core images from tissue microarrays. Conclusion: This automated system, proving reliable as an adjunct pathology tool, has the potential to enhance diagnostic precision and evaluation speed, and might substantially impact cancer treatment planning.

A Paper-Based Multiplexed Serological Test to Monitor Immunity against SARS-COV-2 Using Machine Learning.

The rapid spread of SARS-CoV-2 caused the COVID-19 pandemic and accelerated vaccine development to prevent the spread of the virus and control the disease. Given the sustained high infectivity and evolution of SARS-CoV-2, there is an ongoing interest in developing COVID-19 serology tests to monitor population-level immunity. To address this critical need, we designed a paper-based multiplexed vertical flow assay (xVFA) using five structural proteins of SARS-CoV-2, detecting IgG and IgM antibodies to monitor changes in COVID-19 immunity levels. Our platform not only tracked longitudinal immunity levels but also categorized COVID-19 immunity into three groups: protected, unprotected, and infected, based on the levels of IgG and IgM antibodies. We operated two xVFAs in parallel to detect IgG and IgM antibodies using a total of 40 µL of human serum sample in <20 min per test. After the assay, images of the paper-based sensor panel were captured using a mobile phone-based custom-designed optical reader and then processed by a neural network-based serodiagnostic algorithm. The serodiagnostic algorithm was trained with 120 measurements/tests and 30 serum samples from 7 randomly selected individuals and was blindly tested with 31 serum samples from 8 different individuals, collected before vaccination as well as after vaccination or infection, achieving an accuracy of 89.5%. The competitive performance of the xVFA, along with its portability, cost-effectiveness, and rapid operation, makes it a promising computational point-of-care (POC) serology test for monitoring COVID-19 immunity, aiding in timely decisions on the administration of booster vaccines and general public health policies to protect vulnerable populations.