Stabilizing NiFe sites by high-dispersity of nanosized and anionic Cr species toward durable seawater oxidation.

Electrocatalytic H2 production from seawater, recognized as a promising technology utilizing offshore renewables, faces challenges from chloride-induced reactions and corrosion. Here, We introduce a catalytic surface where OH- dominates over Cl- in adsorption and activation, which is crucial for O2 production. Our NiFe-based anode, enhanced by nearby Cr sites, achieves low overpotentials and selective alkaline seawater oxidation. It outperforms the RuO2 counterpart in terms of lifespan in scaled-up stacks, maintaining stability for over 2500 h in three-electrode tests. Ex situ/in situ analyses reveal that Cr(III) sites enrich OH-, while Cl- is repelled by Cr(VI) sites, both of which are well-dispersed and close to NiFe, enhancing charge transfer and overall electrode performance. Such multiple effects fundamentally boost the activity, selectively, and chemical stability of the NiFe-based electrode. This development marks a significant advance in creating durable, noble-metal-free electrodes for alkaline seawater electrolysis, highlighting the importance of well-distributed catalytic sites.

Advances in targeted therapy for human epidermal growth factor receptor 2 positive in advanced gastric cancer.

Emerging therapeutic methods represented by targeted therapy are effective supplements to traditional first-line chemoradiotherapy resistance. Human epidermal growth factor receptor 2 (HER2) is one of the most important targets in targeted therapy for gastric cancer. Trastuzumab combined with chemotherapy has been used as the first-line treatment for advanced gastric cancer. The safety and efficacy of pertuzumab and margetuximab in the treatment of gastric cancer have been verified. However, monoclonal antibodies, due to their large molecular weight, inability to penetrate the blood-brain barrier, and drug resistance, lead to decreased therapeutic efficacy, so it is necessary to explore the efficacy of other HER2-targeting therapies in gastric cancer. Small-molecule tyrosine kinase inhibitors, such as lapatinib and pyrrotinib, have the advantages of small molecular weight, penetrating the blood-brain barrier and high oral bioavailability, and are expected to become the drugs of choice for perioperative treatment and neoadjuvant therapy of gastric cancer after validation by large-scale clinical trials in the future. Antibo-drug conjugate, such as T-DM1 and T-DXd, can overcome the resistance of monoclonal antibodies despite their different mechanisms of tumor killing, and are a supplement for the treatment of patients who have failed the treatment of monoclonal antibodies such as trastuzumab. Therefore, after more detailed stratification of gastric cancer patients, various gastric cancer drugs targeting HER2 are expected to play a more significant role.

Artificial intelligence for assisted HER2 immunohistochemistry evaluation of breast cancer: A systematic review and meta-analysis.

Accurate assessment of HER2 expression in tumor tissue is crucial for determining HER2-targeted treatment options. Nevertheless, pathologists' assessments of HER2 status are less objective than automated, computer-based evaluations. Artificial Intelligence (AI) promises enhanced accuracy and reproducibility in HER2 interpretation. This study aimed to systematically evaluate current AI algorithms for HER2 immunohistochemical diagnosis, offering insights to guide the development of more adaptable algorithms in response to evolving HER2 assessment practices. A comprehensive data search of the PubMed, Embase, Cochrane, and Web of Science databases was conducted using a combination of subject terms and free text. A total of 4994 computational pathology articles published from inception to September 2023 identifying HER2 expression in breast cancer were retrieved. After applying predefined inclusion and exclusion criteria, seven studies were selected. These seven studies comprised 6867 HER2 identification tasks, with two studies employing the HER2-CONNECT algorithm, two using the CNN algorithm, one with the multi-class logistic regression algorithm, and two using the HER2 4B5 algorithm. AI's sensitivity and specificity for distinguishing HER2 0/1+ were 0.98 [0.92-0.99] and 0.92 [0.80-0.97] respectively. For distinguishing HER2 2+, the sensitivity and specificity were 0.78 [0.50-0.92] and 0.98 [0.93-0.99], respectively. For HER2 3+ distinction, AI exhibited a sensitivity of 0.99 [0.98-1.00] and specificity of 0.99 [0.97-1.00]. Furthermore, due to the lack of HER2-targeted therapies for HER2-negative patients in the past, pathologists may have neglected to distinguish between HER2 0 and 1+, leaving room for improvement in the performance of artificial intelligence (AI) in this differentiation. AI excels in automating the assessment of HER2 immunohistochemistry, showing promising results despite slight variations in performance across different HER2 status. While incorporating AI algorithms into the pathology workflow for HER2 assessment poses challenges in standardization, application patterns, and ethical considerations, ongoing advancements suggest its potential as a widely effective tool for pathologists in clinical practice in the near future.

Preparation of nanocellulose and application of nanocellulose polyurethane composites.

Polyurethane is a widely used material because of its excellent properties. Cellulose is a renewable, biocompatible, and biodegradable natural polymer that also has the advantages of a low density, high porosity, and large specific surface area. There are three main types of common nanocellulose: nanocellulose fibers, cellulose nanocrystals, and bacterial nanocellulose. Composites prepared with nanocellulose and polyurethane materials have good mechanical properties and good biocompatibility and can be applied in sensors, 3D printing, self-repairing materials, electromagnetic shielding, and many other areas. This paper details the preparation processes of different nanocelluloses and the application areas of composites, and points to the future development of nanocellulose polyurethane composites.

Federated attention consistent learning models for prostate cancer diagnosis and Gleason grading.

Artificial intelligence (AI) holds significant promise in transforming medical imaging, enhancing diagnostics, and refining treatment strategies. However, the reliance on extensive multicenter datasets for training AI models poses challenges due to privacy concerns. Federated learning provides a solution by facilitating collaborative model training across multiple centers without sharing raw data. This study introduces a federated attention-consistent learning (FACL) framework to address challenges associated with large-scale pathological images and data heterogeneity. FACL enhances model generalization by maximizing attention consistency between local clients and the server model. To ensure privacy and validate robustness, we incorporated differential privacy by introducing noise during parameter transfer. We assessed the effectiveness of FACL in cancer diagnosis and Gleason grading tasks using 19,461 whole-slide images of prostate cancer from multiple centers. In the diagnosis task, FACL achieved an area under the curve (AUC) of 0.9718, outperforming seven centers with an average AUC of 0.9499 when categories are relatively balanced. For the Gleason grading task, FACL attained a Kappa score of 0.8463, surpassing the average Kappa score of 0.7379 from six centers. In conclusion, FACL offers a robust, accurate, and cost-effective AI training model for prostate cancer pathology while maintaining effective data safeguards.

Oxalate anions-intercalated NiFe layered double hydroxide as a highly active and stable electrocatalyst for alkaline seawater oxidation.

Seawater electrolysis is gaining recognition as a promising method for hydrogen production. However, severe anode corrosion caused by the high concentration of chloride ions (Cl-) poses a challenge for the long-term oxygen evolution reaction. Herein, an anti-corrosion strategy of oxalate anions intercalation in NiFe layered double hydroxide on nickel foam (NiFe-C2O42- LDH/NF) is proposed. The intercalation of these highly negatively charged C2O42- serves to establish electrostatic repulsion and impede Cl- adsorption. In alkaline seawater, NiFe-C2O42- LDH/NF requires an overpotential of 337 mV to gain the large current density of 1000 mA cm-2 and operates continuously for 500 h. The intercalation of C2O42- is demonstrated to significantly boost the activity and stability of NiFe LDH-based materials during alkaline seawater oxidation.

Multi-Agent Graph-Attention Deep Reinforcement Learning for Post-Contingency Grid Emergency Voltage Control.

Grid emergency voltage control (GEVC) is paramount in electric power systems to improve voltage stability and prevent cascading outages and blackouts in case of contingencies. While most deep reinforcement learning (DRL)-based paradigms perform single agents in a static environment, real-world agents for GEVC are expected to cooperate in a dynamically shifting grid. Moreover, due to high uncertainties from combinatory natures of various contingencies and load consumption, along with the complexity of dynamic grid operation, the data efficiency and control performance of the existing DRL-based methods are challenged. To address these limitations, we propose a multi-agent graph-attention (GATT)-based DRL algorithm for GEVC in multi-area power systems. We develop graph convolutional network (GCN)-based agents for feature representation of the graph-structured voltages to improve the decision accuracy in a data-efficient manner. Furthermore, a cutting-edge attention mechanism concentrates on effective information sharing among multiple agents, synergizing different-sized subnetworks in the grid for cooperative learning. We address several key challenges in the existing DRL-based GEVC approaches, including low scalability and poor stability against high uncertainties. Test results in the IEEE benchmark system verify the advantages of the proposed method over several recent multi-agent DRL-based algorithms.

Concordance of assessments of four PD-L1 immunohistochemical assays in esophageal squamous cell carcinoma (ESCC).

OBJECTIVE: Given real-world limitations in programmed death-ligand 1 (PD-L1) testing, concordance studies between PD-L1 assays are needed. We undertook comparisons of PD-L1 assays (DAKO22C3, Ventana SP263, Ventana SP142, E1L3N) among observers in esophageal squamous cell carcinoma (ESCC) to provide information on the analytical and clinical comparability of four PD-L1 IHC assays. METHODS: Paraffin embedded samples of 50 cases of esophageal squamous cell carcinoma were obtained, satined with all four PD-L1 assays. PD-L1 was evaluated by 68 pathologists from 19 different hospitals. PD-L1 expression was assessed for combined positive score (CPS). RESULTS: The expression sensitivity of SP263 was the highest in ESCC, followed by 22C3, E1L3N and SP142. Taking CPS 10 as the critical value, inter-observer concordance for CPS scores among 68 physicians was assessed for the 22C3, SP263, SP142, and E1L3N assays, yielding values of 0.777, 0.790, 0.758, and 0.782, respectively. In the comparison between assays, the overall CPS scores concordance rates between 22C3 and SP263, SP142, and E1L3N were 0.896, 0.833, and 0.853, respectively. 22C3 and SP263 have high concordance, with OPA of 0.896, while E1L3N and SP142 have the highest concordance, with OPA of 0.908. CONCLUSION: In ESCC, the concordance of PD-L1 evaluation among observers is good, and the immune cell score is still an important factor affecting the concordance of interpretation among observers. Cases near the specific threshold are still the difficult problem of interpretation. SP263 had the highest CPS score of the four assays. SP263 cannot identify all 22C3 positive cases, but had good concordance with 22C3.E1L3N and SP142 showed high concordance.

Computed tomography radiomics identification of T1-2 and T3-4 stages of esophageal squamous cell carcinoma: two-dimensional or three-dimensional?

BACKGROUND: To evaluate two-dimensional (2D) and three-dimensional (3D) computed tomography (CT) radiomics analysis for the T stage of esophageal squamous cell carcinoma (ESCC). METHODS: 398 patients with pathologically confirmed ESCC were divided into training and testing sets. All patients underwent chest CT scans preoperatively. For each tumor, based on CT images, a 2D region of interest (ROI) was outlined on the largest cross-sectional area, and a 3D ROI was outlined layer by layer on each section of the tumor. The radiomics platform was used for feature extraction. For feature selection, stepwise logistic regression was used. The receiver operating characteristic (ROC) curve was used to assess the diagnostic performance of the 2D radiomics model versus the 3D radiomics model. The differences were compared using the DeLong test. The value of the clinical utility of the two radiomics models was evaluated. RESULTS: 1595 radiomics features were extracted. After screening, two radiomics models were constructed. In the training set, the difference between the area under the curve (AUC) of the 2D radiomics model (AUC = 0.831) and the 3D radiomics model (AUC = 0.830) was not statistically significant (p = 0.973). In the testing set, the difference between the AUC of the 2D radiomics model (AUC = 0.807) and the 3D radiomics model (AUC = 0.797) was also not statistically significant (p = 0.748). A 2D model was equally useful as a 3D model in clinical situations. CONCLUSION: The performance of 2D radiomics model is comparable to that of 3D radiomics model in distinguishing between the T1-2 and T3-4 stages of ESCC. In addition, 2D radiomics model may be a more feasible option due to the shorter time required for segmenting the ROI.

Clinicopathological features and prognostic analysis of HER2 low and fibrotic focus in HER2-negative breast cancer.

OBJECTIVE: The aim of this study is to evaluate the clinicopathological features and prognostic significance of HER2 low, fibrotic focus (FF), and tumor-infiltrating lymphocytes (TILs) in patients with HER2-negative breast cancer. METHODS: We retrospectively reviewed the data of 293 patients with HER2-negative, stage I-II, invasive breast cancer of non-specific types. The HER2-negative cases were classified into HER2 low and HER2 0. Digital analysis of hematoxylin-eosin stained whole slide images was used to evaluate the FF expression. TILs were also evaluated using the Whole Slide Image. Furthermore, the association between HER2 low, FF, and TILs as well as their prognostic significance were analyzed. RESULTS: The study cohort included 178 cases (60.8%) with HER2 low and 115 cases (39.2%) with HER2 0. Older age, lower Nottingham histological grade (NHG), estrogen receptor (ER) positivity, progesterone receptor (PR) positivity, and hormone receptor (HR) positivity were all associated with HER2 low. FF was correlated with older age, intermediate and low NHG, vascular invasion, HR positivity, HER2 low status, high Ki67 expression, and low TILs. Univariate survival analysis showed that FF was significantly associated with shorter progression-free survival (PFS). Stratified analysis indicated that in the HR-negative and HR-positive groups, HER2 status and TILs did not affect PFS. DFS was longer in patients without FF compared to those with FF in the HR-positive (hazard ratio [HR] = 0.313) and HER2 low (HR = 0.272) groups. DFS was also significantly longer in patients without FF compared to those with FF in the HR-negative (HR = 0.069) and HER2 0 groups (HR = 0.129). CONCLUSION: The results indicated that the HER2 low status and the TILs expression did not impact prognosis. However, patients with FF exhibited distinct biological characteristics and prognostic significance, particularly in the HR-negative and HER2 0 groups. This provides a rationale for accurate diagnosis and treatment of HER2-negative breast cancer.

[Mechanism of protective effect of resveratrol on poor ovarian response in mice].

This study aims to investigate the therapeutic effects and potential mechanisms of resveratrol(Res) on poor ovarian response(POR) in mice. The common target genes shared by Res and POR were predicted by network pharmacology, used for Gene Ontology(GO) annotation and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment, and then validated by animal experiments. The mice with regular estrous cycle after screening were randomized into normal, POR, and low-and high-dose(20 and 40 mg·kg~(-1), respectively) Res groups. The normal group was administrated with an equal volume of 0.9% sodium chloride solution by gavage, and the mice in other groups with tripterygium glycosides suspension(50 mg·kg~(-1)) by gavage for 2 weeks. After the modeling, the mice in low-and high-dose Res groups were treated with Res by gavage for 2 weeks, and the mice in normal and POR groups with an equal volume of 0.9% sodium chloride solution by gavage. Ovulation induction and sample collection were carried out on the day following the end of treatment. Vaginal smears were collected for observation of the changes in the estrous cycle, the counting of retrieved oocytes, and the measurement of ovarian wet weight and ovarian index. The enzyme-linked immunosorbent assay(ELISA) was employed to measure the levels of anti-mullerian hormone(AMH), follicle-stimulating hormone(FSH), estradiol(E_2), and luteinizing hormone(LH) in the serum. The ovarian tissue morphology and granulosa cell apoptosis were observed by hematoxylin-eosin(HE) staining and terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling(TUNEL), respectively. Western blot was employed to determine the protein levels of phosphatidylinositol 3-kinase(PI3K), protein kinase B(AKT), forkhead box O(FOXO) 3a, hypoxia-inducible factor(HIF)-1α, B-cell lymphoma-2(Bcl-2), and Bcl-2-associated X protein(Bax). A total of 222 common targets shared by Res and POR were collected. GO annotation indicated that these targets were mainly involved in oxidative stress response. KEGG enrichment analysis revealed that Res can intervene in POR via PI3K/AKT, HIF-1, and FOXO signaling pathways. Animal experiments showed that the model group had higher rate of estrous cycle disorders, lower number and poorer morphology of normally developed follicles at all levels, more atretic follicles, higher apoptosis of ovarian granulosa cells, lower number of retrieved oocytes, lower ovarian wet weight and ovarian index, higher serum levels of FSH and LH, lower levels of AMH and E_2, higher expression levels of HIF-1α, FOXO3a and Bax, and lower expression levels of PI3K, AKT, and Bcl-2 in the ovarian tissue than the normal group. Compared with the POR group, low-and high-dose Res decreased the rate of estrous cycle disorders, improved the follicle number and morphology, reduced atretic follicles, promoted the apoptosis of ovarian granulosa cells, increased retrieved oocytes, ovarian wet weight and ovarian index, and lowered serum FSH and LH levels. Moreover, Res down-regulated the expression levels of HIF-1α, FOXO3a and Bax, and up-regulated the expression levels of PI3K, AKT and Bcl-2 in the ovarian tissue. In summary, Res can inhibit apoptosis and mitigate poor ovarian response in mice by regulating the PI3K/AKT/FOXO3a and HIF-1α pathways.

Qualitative and Quantitative Analysis of Five Indoles or Indazole Amide Synthetic Cannabinoids in Suspected E-Cigarette Oil by GC-MS.

OBJECTIVES: To establish the GC-MS qualitative and quantitative analysis methods for the synthetic cannabinoids, its main matrix and additives in suspicious electronic cigarette (e-cigarette) oil samples. METHODS: The e-cigarette oil samples were analyzed by GC-MS after diluted with methanol. Synthetic cannabinoids, its main matrix and additives in e-cigarette oil samples were qualitatively analyzed by the characteristic fragment ions and retention time. The synthetic cannabinoids were quantitatively analyzed by using the selective ion monitoring mode. RESULTS: The linear range of each compound in GC-MS quantitative method was 0.025-1 mg/mL, the matrix recovery rate was 94%-103%, the intra-day precision relative standard deviations (RSD) was less than 2.5%, and inter-day precision RSD was less than 4.0%. Five indoles or indazole amide synthetic cannabinoids were detected in 25 e-cigarette samples. The main matrixes of e-cigarette samples were propylene glycol and glycerol. Additives such as N,2,3-trimethyl-2-isopropyl butanamide (WS-23), glycerol triacetate and nicotine were detected in some samples. The content range of synthetic cannabinoids in 25 e-cigarette samples was 0.05%-2.74%. CONCLUSIONS: The GC-MS method for synthesizing cannabinoid, matrix and additive in e-cigarette oil samples has good selectivity, high resolution, low detection limit, and can be used for simultaneous qualitative and quantitative analysis of multiple components; The explored fragment ion fragmentation mechanism of the electron bombardment ion source of indole or indoxamide compounds helps to identify such substances or other compounds with similar structures in cases.

Establishment and Modification of Ninety-seven Pneumococcal Serotyping Assays Based on Quantitative Real-time Polymerase Chain Reaction.

Objective: To establish and modify quantitative real-time polymerase chain reaction (qPCR)-based serotyping assays to distinguish 97 pneumococcal serotypes. Methods: A database of capsular polysaccharide ( cps) loci sequences was generated, covering 97 pneumococcal serotypes. Bioinformatics analyses were performed to identify the cps loci structure and target genes related to different pneumococcal serotypes with specific SNPs. A total of 27 novel qPCR serotyping assay primers and probes were established based on qPCR, while 27 recombinant plasmids containing serotype-specific DNA sequence fragments were constructed as reference target sequences to examine the specificity and sensitivity of the qPCR assay. A panel of pneumococcal reference strains was employed to evaluate the capability of pneumococcal serotyping. Results: A total of 97 pneumococcal serotyping assays based on qPCR were established and modified, which included 64 serotypes previously reported as well as an additional 33 serotypes. Twenty-seven novel qPCR serotyping target sequences were implemented in the pneumococcal qPCR serotyping system. A total of 97 pneumococcal serotypes, which included 52 individual serotypes and 45 serotypes belonging to 20 serogroups, could not be identified as individual serotypes. The sensitivity of qPCR assays based on 27 target sequences was 1-100 copies/µL. The specificity of the qPCR assays was 100%, which were tested by a panel of 90 serotypes of the pneumococcal reference strains. Conclusion: A total of 27 novel qPCR assays were established and modified to analyze 97 pneumococcal serotypes.

Chromium doping enabled improvement in alkaline seawater oxidation over cobalt carbonate hydroxide nanowire array.

The presence of chlorine species in seawater can cause severe anode corrosion, highlighting the critical need for the design of efficient and robust electrocatalysts towards the oxygen evolution reaction (OER) for hydrogen production. Herein, we present a chromium doped cobalt carbonate hydroxide nanowire array on nickel foam (Cr-CoCH/NF) as an effective OER electrocatalyst in seawater. In alkaline conditions, Cr-CoCH/NF exhibits a low overpotential of 450 mV to achieve 500 mA cm-2, surpassing that of CoCH/NF (614 mV). Additionally, it demonstrates 200 h of continuous oxygen evolution testing.

Multi-center study on predicting breast cancer lymph node status from core needle biopsy specimens using multi-modal and multi-instance deep learning.

The objective of our study is to develop a deep learning model based on clinicopathological data and digital pathological image of core needle biopsy specimens for predicting breast cancer lymph node metastasis. We collected 3701 patients from the Fourth Hospital of Hebei Medical University and 190 patients from four medical centers in Hebei Province. Integrating clinicopathological data and image features build multi-modal and multi-instance (MMMI) deep learning model to obtain the final prediction. For predicting with or without lymph node metastasis, the AUC was 0.770, 0.709, 0.809 based on the clinicopathological features, WSI and MMMI, respectively. For predicting four classification of lymph node status (no metastasis, isolated tumor cells (ITCs), micrometastasis, and macrometastasis), the prediction based on clinicopathological features, WSI and MMMI were compared. The AUC for no metastasis was 0.770, 0.709, 0.809, respectively; ITCs were 0.619, 0.531, 0.634, respectively; micrometastasis were 0.636, 0.617, 0.691, respectively; and macrometastasis were 0.748, 0.691, 0.758, respectively. The MMMI model achieved the highest prediction accuracy. For prediction of different molecular types of breast cancer, MMMI demonstrated a better prediction accuracy for any type of lymph node status, especially in the molecular type of triple negative breast cancer (TNBC). In the external validation sets, MMMI also showed better prediction accuracy in the four classification, with AUC of 0.725, 0.757, 0.525, and 0.708, respectively. Finally, we developed a breast cancer lymph node metastasis prediction model based on a MMMI model. Through all cases tests, the results showed that the overall prediction ability was high.

Characterization and Antibacterial Properties of Egg White Protein Films Loaded with ε-Polylysine: Evaluation of Their Degradability and Application.

There is an ongoing trend to design new kinds of food packaging materials with excellent properties which are environmentally friendly enough. The aim of this study was to prepare and characterize egg white protein (EWP)-based composite films with and without ε-polylysine (Lys), as well as to compare their physical-chemical properties, structural properties, degradation and antibacterial properties. The results showed that with the addition of Lys, the composite films showed a decreasing tendency of the water permeability due to the enhanced interaction between proteins and water molecules. As indicated by the structural properties, stronger cross-linking and intermolecular interactions happened with increasing concentration of Lys. In addition, the composite films presented excellent antibacterial activities against Escherichia coli and Staphylococcus aureus on chilled pork in the presence of Lys. Therefore, our prepared films might be used as a freshness-keeping material with an application in meat preservation. The biodegradation evaluation demonstrated that the composite films were environmental-friendly and have potential applications in the field of food packaging.

RT-qPCR is helpful to distinguish the clinicopathological features of HER2 immunohistochemistry 0 and 1.

The most commonly applied techniques to assess human epidermal growth factor receptor 2 (HER2) expression in breast cancer are immunohistochemistry (IHC) and fluorescence in situ hybridization (FISH). HER2 detection by reverse transcription quantitative polymerase chain reaction (RT-qPCR) can provide standardized, objective and automated assessment and reflect the HER2 expression continuity. Currently, there is lack of sufficient evidence to validate whether RT­qPCR technique is more appropriate for the detection of HER2 low expression, especially ultra-low expression. Here, we primarily utilized RT-qPCR to differentiate HER2 true negative, ultra-low and 1 +, and compare the clinicopathological features and prognosis between RT-qPCR and IHC. 136 breast cancer cases with HER2 0 or 1 + were collected, also included 21 cases with HER2 2 + FISH negative as well as 25 cases with HER2 positive during the same period for comparative analysis. Compared the mRNA levels based on IHC/FISH scores. The receiver operating characteristic (ROC) curve was utilized to determine the threshold for reclassification, and the clinicopathological characteristics and prognosis differences among IHC true negative, ultra-low and 1 + after re-classification by RT-qPCR were analyzed. The mRNA level significantly differed between the IHC 0 and 1 + groups (p < 0.001). The IHC 0 group was further divided into true negative and ultra-low, there was no statistically significant difference in mRNA levels between true negative and ultra-low groups, while the difference between ultra-low and 1 + mRNA levels was statistically significant (p < 0.001). After reclassification of IHC true negative, ultra-low and 1 + by RT-qPCR, there were statistically significant differences in histological grade, ER, PR and TILs expression. There was no significant difference between DFS and OS in the two classification methods. RT-qPCR classification aids in distinguishing clinicopathological characteristics and can serve as a supplementary technique for detecting HER2-low by IHC.

Improved Alkaline Seawater Splitting of NiS Nanosheets by Iron Doping.

Seawater electrolysis driven by renewable electricity is deemed a promising and sustainable strategy for green hydrogen production, but it is still formidably challenging. Here, we report an iron-doped NiS nanosheet array on Ni foam (Fe-NiS/NF) as a high-performance and stable seawater splitting electrocatalyst. Such Fe-NiS/NF catalyst needs overpotentials of only 420 and 270 mV at 1000 mA cm-2 for the oxygen evolution reaction and hydrogen evolution reaction in alkaline seawater, respectively. Furthermore, its two-electrode electrolyzer needs a cell voltage of 1.88 V for 1000 mA cm-2 with 50 h of long-term electrochemical durability in alkaline seawater. Additionally, in situ electrochemical Raman and infrared spectroscopy were employed to detect the reconstitution process of NiOOH and the generation of oxygen intermediates under reaction conditions.