Validation of large language models for detecting pathologic complete response in breast cancer using population-based pathology reports.

AIMS: The primary goal of this study is to evaluate the capabilities of Large Language Models (LLMs) in understanding and processing complex medical documentation. We chose to focus on the identification of pathologic complete response (pCR) in narrative pathology reports. This approach aims to contribute to the advancement of comprehensive reporting, health research, and public health surveillance, thereby enhancing patient care and breast cancer management strategies. METHODS: The study utilized two analytical pipelines, developed with open-source LLMs within the healthcare system's computing environment. First, we extracted embeddings from pathology reports using 15 different transformer-based models and then employed logistic regression on these embeddings to classify the presence or absence of pCR. Secondly, we fine-tuned the Generative Pre-trained Transformer-2 (GPT-2) model by attaching a simple feed-forward neural network (FFNN) layer to improve the detection performance of pCR from pathology reports. RESULTS: In a cohort of 351 female breast cancer patients who underwent neoadjuvant chemotherapy (NAC) and subsequent surgery between 2010 and 2017 in Calgary, the optimized method displayed a sensitivity of 95.3% (95%CI: 84.0-100.0%), a positive predictive value of 90.9% (95%CI: 76.5-100.0%), and an F1 score of 93.0% (95%CI: 83.7-100.0%). The results, achieved through diverse LLM integration, surpassed traditional machine learning models, underscoring the potential of LLMs in clinical pathology information extraction. CONCLUSIONS: The study successfully demonstrates the efficacy of LLMs in interpreting and processing digital pathology data, particularly for determining pCR in breast cancer patients post-NAC. The superior performance of LLM-based pipelines over traditional models highlights their significant potential in extracting and analyzing key clinical data from narrative reports. While promising, these findings highlight the need for future external validation to confirm the reliability and broader applicability of these methods.

Longitudinal associations of dietary fiber and its source with 48-week weight loss maintenance, cardiometabolic risk factors and glycemic status under metformin or acarbose treatment: a secondary analysis of the March randomized trial.

AIMS: To examine longitudinal and dose-d ependent associations between dietary fiber intake and various clinical outcomes over 48 weeks of pharmacological treatment in T2DM patients. METHODS: In this secondary analysis, we used data from the MARCH trial, which was designed to compare the efficacy of acarbose or metformin monotherapy as the initial therapy in Chinese patients newly diagnosed with T2DM. Dietary data were obtained using a 24-h dietary recall method to evaluate the intakes of dietary fiber from different sources as well as the carbohydrate-to-fiber ratio. RESULTS: A total of 551 newly-diagnosed patients with T2DM complete dietary records (286 in the acarbose group and 265 in the metformin group) were included. Higher intake of total fiber and whole grain fiber was positively associated with better ß-cell function, insulin sensitivity and postprandial glycemic control under acarbose treatment. Higher intake of legume fiber was associated with better glycemic control under both acarbose and metformin treatment but with better weight loss only under metformin treatment. A high-carbohydrate-low-fiber diet was associated with worse glycemic control and lower HDL-C under acarbose treatment but with higher insulin sensitivity and better weight loss under metformin treatment. CONCLUSIONS: The notable effects of various dietary fibers when combined with different oral glucose-lowering medications should be considered to maximize therapeutic benefit.

trajPredRNN+: A new approach for precipitation nowcasting with weather radar echo images based on deep learning.

：Short-term rainfall prediction is a crucial and practical research area, with the accuracy of rainfall prediction, particularly for heavy rainfall, significantly impacting people's lives, property, and even their safety. Existing models, such as ConvLSTM, TrajGRU, and PredRNN, exhibit limitations in capturing fine-grained appearances due to insufficient memory units or addressing positional misalignment issues, thereby compromising the accuracy of model predictions. In this study, we propose trajPredRNN+, an innovative approach that integrates the trajectory segmentation model and the PredRNN deep learning model to address both limitations in nowcasting precipitation using weather radar echo images. By incorporating attention mechanisms, the model demonstrates an enhanced focus on short-term and imminent heavy rainfall events. To ensure improved stability during training, a residual network is introduced. Lastly, a more rational and effective training loss function is proposed, encompassing weight mechanism, SSIM index, and GAN loss. To validate the proposed model, we conducted a comparative experiment and an ablation experiment using the radar echo map dataset obtained from the Shenzhen Meteorological Bureau. The results of these experiments demonstrate that our model has achieved significant improvements across multiple key performance indicators.

Genomic analysis of hypoxia-tolerant population of the Chinese mitten crab (Eriocheir sinensis).

Hypoxic stress, triggered by a multitude of factors, has inflicted significant economic repercussions on the aquaculture of Eriocheir sinensis. In this research, we sequenced a collective of 60 samples from both hypoxia-sensitive and hypoxia-resistant groups utilizing streamlined genome sequencing techniques. Subsequently, we delved into population evolution, scrutinized the selective sweep within these populations, and performed a genome-wide association study (GWAS) focused on the hypoxia tolerance traits within the population, all through the lens of SNPs molecular markers. This comprehensive analysis aimed to uncover the SNPs and pinpoint the pertinent candidate genes that influence the hypoxia tolerance capabilities of E. sinensis. The selective sweep analysis revealed that genes harboring potential genetic variations within the two populations were predominantly enriched in areas such as signaling molecules and interactions, energy metabolism, glycolipid metabolism, and immune response. In the genome-wide association study focusing on hypoxia tolerance traits, we identified four SNPs significantly associated with hypoxia resistance. Furthermore, one potential candidate gene, Dscam2, which is believed to influence hypoxia tolerance, was discovered within a 50 kb vicinity of these SNPs. These identified SNPs can serve as molecular markers for screening hypoxia tolerance, offering valuable insights for the genetic improvement of E. sinensis.

Role of Agrin in tissue repair and regeneration: From mechanisms to therapeutic opportunities (Review).

Tissue regeneration is a complex process that involves the recruitment of various types of cells for healing after injury; it is mediated by numerous precise interactions. However, the identification of effective targets for improving tissue regeneration remains a challenge. As an extracellular matrix protein, Agrin plays a critical role in neuromuscular junction formation. Furthermore, recent studies have revealed the role of Agrin in regulating tissue proliferation and regeneration, which contributes to the repair process of injured tissues. An in­depth understanding of the role of Agrin will therefore be of value. Given that repair and regeneration processes occur in various parts of the human body, the present systematic review focuses on the role of Agrin in typical tissue and highlights the potential signaling pathways that are involved in Agrin­induced repair and regeneration. This review offers important insight into novel strategies for the future clinical applications of Agrin­based therapies, which may represent a feasible treatment option for patients who require organ replacement or repair.

Deep learning detection of hand motion during microvascular anastomosis simulations performed by expert cerebrovascular neurosurgeons.

OBJECTIVE: Deep learning enables precise hand tracking without the need for physical sensors, allowing for unsupervised quantitative evaluation of surgical motion and tasks. We quantitatively assessed the hand motions of experienced cerebrovascular neurosurgeons during simulated microvascular anastomosis using deep learning. We explored the extent to which surgical motion data differed among experts. METHODS: A deep learning detection system tracked 21 landmarks corresponding to digit joints and the wrist on each hand of 5 expert cerebrovascular neurosurgeons. Tracking data for each surgeon was analyzed over long and short time intervals to examine gross movements and micromovements, respectively. Quantitative algorithms assessed the economy and flow of motion by calculating mean movement distances from the baseline median landmark coordinates and median times between sutures, respectively. RESULTS: Tracking data correlated with specific surgical actions observed in microanastomosis video analysis. Economy of motion during suturing was calculated as 19, 26, 29, 27, and 28 pixels for surgeons 1, 2, 3, 4, and 5, respectively. Flow of motion during microanastomosis was 31.96, 29.40, 28.90, 7.37, and 47.21 secs for surgeons 1, 2, 3, 4, and 5, respectively. CONCLUSIONS: Hand tracking data showed similarities among experts, with low movements from baseline, minimal excess motion, and rhythmic suturing patterns. The data revealed unique patterns related to each expert's habits and techniques. The results showed that surgical motion can be correlated with hand motion and assessed using mathematical algorithms. We also demonstrated the feasibility and potential of deep learning-based motion detection to enhance surgical training.

Aspirin increases estrogen levels in the placenta to prevent preeclampsia by regulating placental metabolism and transport function.

Preeclampsia is a unique multisystem progressive disease during pregnancy, which seriously endangers the health of pregnant women and fetuses. In clinical practice, aspirin is recommended for the prevention of preeclampsia, but the mechanism by which aspirin prevents preeclampsia has not yet been revealed. This report comprehensively evaluates the effects of aspirin on the expression and activity of placental metabolic enzymes and transporters. We found that after aspirin administration, only the expression of organic anion transporter 4 (OAT4) in the placenta showed a significant increase at both mRNA and protein levels, consistent with the results in JAR cells. Meanwhile, studies on the metabolic enzyme activity in the placenta showed a high upregulation of CYP19A1 activity. Subsequently, significant increases in endogenous substrates of OAT4 and CYP19A1 (dehydroepiandrosterone sulfate (DHEAS) and androstenedione) as well as estrone were detected in placental tissue. In summary, aspirin enhances the transport of DHEAS through OAT4 and promotes the metabolism of androstenedione through CYP19A1, thereby increasing estrogen levels in the placenta. This may be the mechanism by which aspirin prevents preeclampsia and maintains pregnancy by regulating the metabolism and transport function of the placenta.

Prostate cancer treatment recommendation study based on machine learning and SHAP interpreter.

This study utilized data from 140,294 prostate cancer cases from the Surveillance, Epidemiology, and End Results (SEER) database. Here, 10 different machine learning algorithms were applied to develop treatment options for predicting patients with prostate cancer, differentiating between surgical and non-surgical treatments. The performances of the algorithms were measured using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, positive predictive value, negative predictive value. The Shapley Additive Explanations (SHAP) method was employed to investigate the key factors influencing the prediction process. Survival analysis methods were used to compare the survival rates of different treatment options. The CatBoost model yielded the best results (AUC = 0.939, sensitivity = 0.877, accuracy = 0.877). SHAP interpreters revealed that the T stage, cancer stage, age, cores positive percentage, prostate-specific antigen, and Gleason score were the most critical factors in predicting treatment options. The study found that surgery significantly improved survival rates, with patients undergoing surgery experiencing a 20.36% increase in 10-year survival rates compared with those receiving non-surgical treatments. Among surgical options, radical prostatectomy had the highest 10-year survival rate at 89.2%. This study successfully developed a predictive model to guide treatment decisions for prostate cancer. Moreover, the model enhanced the transparency of the decision-making process, providing clinicians with a reference for formulating personalized treatment plans.

Correlation analysis of cofilin-1 with renal prognosis in primary IgA nephropathy.

PURPOSE: The purpose of this study was to investigate the correlation between podocyte related biomarker cofilin-1 and renal function, and explore the value of cofilin-1 in predicting the risk of renal adverse prognosis in IgA nephropathy (IgAN). METHODS: Patients with primary IgAN diagnosed by initial renal biopsy performed in our hospital from January 2019 to February 2022 were included. This study was a prospective cohort study. All IgAN patients were detected the expression of cofilin-1 and other related biomarkers (RhoA, NGAL) in urine by enzyme-linked immunosorbent assay (ELISA) and follow-up at least 6 months. We also collected baseline clinicopathologial data of IgAN. The decreased renal function group was defined as baseline eGFR < 60 ml/min/1.73m2. Logistic and Cox regression model were used to analyze the correlation among cofilin-1 and renal prognosis. RESULTS: 133 IgAN patients were included, with a male-to-female ratio of 1.25:1 and an age of 37.67 ± 13.78 years, as well as an average of eGFR was 71.63 (40.42,109.33) ml/min/1.73m2. 56 patients (42.1%) had decreased renal function at baseline, with the average of eGFR was 34.07 (16.72, 49.21) ml/min/1.73 m2. 12 of which developed to renal adverse prognosis. The average of follow-up time was 22.035 ± 8.992 months. The multivariate regression analysis showed that increased urinary cofilin-1 was an independent risk factor associated with baseline renal function decline and renal adverse prognosis in IgAN patients (P < 0.05). ROC curves showed great efficacy of urinary cofilin-1 levels in diagnosing baseline renal function decline and predicting renal adverse prognosis (the area under the ROC curve was 0.708 and 0.803). CONCLUSION: Cofilin-1 as a novel biomarker of podocyte lesion is closely related to renal function decline in IgAN. Cofilin-1 has certain clinical value in predicting the risk of renal adverse prognosis. Podocyte fusion affects the renal prognosis of IgAN.

Exploring the behavioral intentions of PICC-related thrombosis prevention in breast cancer patients undergoing chemotherapy: a qualitative study based on theory of planned behavior.

PURPOSE: To explore the behavioral intention of breast cancer patients undergoing chemotherapy to prevent PICC-related thrombosis based on the theory of planned behavior (TPB). METHODS: This qualitative study employed purposive sampling and conducted semi-structured interviews with 14 breast cancer patients undergoing chemotherapy in the outpatient chemotherapy ward of a tertiary A-level comprehensive hospital in Beijing from July to August 2023. Data were analyzed using Colaizzi's descriptive analysis framework. RESULTS: Data analysis identified 10 themes that were derived from 4 aspects. Regarding behavioral attitude, three themes were condensed: (1) Considering the benefits of preventive measures, (2) Simple and easy preventive measures, and (3) Underestimating the importance of PICC-related thrombosis prophylaxis. Subjective norms yielded two main themes and five sub-themes: (1) Support from those close to the patient motivates adherence to prophylaxis (support from the patient's family, healthcare professionals, and other patients) and (2) Patients are influenced by personal factors to form an internal driving force (physical symptoms, fear of PICC-related thrombosis). Regarding perceived behavioral control, three main themes and four sub-themes were extracted: (1) Obstacles before actual prevention exercise (prevention information, hard-to-remember information), (2) Forgetfulness is the main obstacle factor, and (3) Wanting to overcome barriers to adhere to regular prevention (confidence to overcome obstacles, hope to get support). CONCLUSIONS: The impediments and facilitators identified in this study may provide a scientific foundation for subsequent targeted non-pharmacological preventive interventions for PICC-related thrombosis based on TPB in breast cancer patients undergoing chemotherapy. Special interventions should be designed for the patients in three areas: the patients themselves, the supporters around the patient, and the healthcare professionals.

Global, regional, and national burden of inflammatory bowel disease, 1990-2021: Insights from the global burden of disease 2021.

PURPOSE: The prevalence of inflammatory bowel disease (IBD) is on the rise worldwide. We utilizes data from the Global Burden of Diseases (GBD) 2021 to analyze the national-level burden of IBD, trends in disease incidence, and epidemiological characteristics. METHODS: Detailed information on IBD was gathered from 204 countries and territories spanning 1990 to 2021, sourced from the GBD 2021. Calculations were performed for incidence rates, mortality rates, disease-adjusted life years (DALYs), and estimated annual percentage changes (EAPCs). These trends were analyzed based on region, nationality, age, gender, and World Bank income level stratifications. RESULTS: The global age-standardised incident rate (ASIR) of IBD increased from 4.22 per 100000 in 1990 to 4.45 per 100000 in 2021. However, the age-standardised mortality rate (ASMR) decreased from 0.60 per 100000 in 1990 to 0.52 per 100000 in 2021. Similarly, the age-standardised DALYs rate decreased from 21.55 per 100000 in 1990 to 18.07 per 100000 in 2021. Gender comparisons showed negligible differences in disease burden. The greatest increase in IBD-associated ASIR and ASMR occurred in World Bank upper-middle income region (EAPCs, 1.25) and World Bank high-income region (EAPCs, 1.00), respectively. Regionally, East Asia experienced the largest increase in ASIR (EAPCs, 2.89). Among 204 countries, China had the greatest increases in ASIR (EAPCs, 2.93), Netherlands had the highest ASMR in 2021 (2.21 per 100000). CONCLUSIONS: Global incidence rate of IBD have been increasing from 1990 to 2021, while the DALYs and mortality have been decreasing. The escalating incident rates in select Asian regions deserves further attention.

Electrochemically Driven Denitrative Cyanation of Nitroarenes.

A practical denitrative cyanation of feedstock nitroarenes under mild and transition metal-free reaction conditions has been developed. The key to success lies in the use of electrochemically driven, inexpensive ionic liquid N-methylimidazolium p-toluenesulfonate-promoted selective cathode reduction of nitroarenes to anilines, followed by diazoation, cathode reduction to form the aryl radical, and the essential radical cyanation process in one pot. Our protocol shows broad functional group tolerance and can be applied for the modification of bioactive targets.

Melatonin downregulates angiogenesis and lymphangiogenesis by regulating tumor-associated macrophages via NLRP3 inflammasomes in lung adenocarcinoma.

Tumor-associated macrophages (TAMs), present within the tumor microenvironment (TME), strictly modulate tumor angiogenesis and lymphangiogenesis. Nevertheless, the associated signaling networks and candidate drug targets for these events remains to be elucidated. Given its antioxidative activities, we speculated that melatonin may reduce pyroptosis, and thereby modulate both angiogenesis and lymphangiogenesis. We revealed that a co-culture of A549 cells and THP-1 macrophages strongly enhanced expressions of the NLRP3 inflammasome axis members, and augmented angiogenesis and lymphangiogenesis. Next, we overexpressed NLRP3 in the A549 cells, and demonstrated that excess NLRP3 expression substantially upregulated VEGF and CXCL cytokine expressions, and enhanced lymphatic endothelial cells (LECs) tube formation. In contrast, NLRP3 inhibition produced the opposite effect. In addition, relative to controls, melatonin administration strongly inhibited the NLRP3 inflammasome axis, as well as angiogenesis and lymphangiogenesis in the co-culture system. Subsequent animal experiments using a Lewis Lung Carcinoma (LLC) subcutaneous tumor model in mice corroborate these findings. Melatonin treatment and NLRP3 knockdown significantly inhibit tumor growth and downregulate NLRP3 and IL-1ß expression in tumor tissues. Furthermore, melatonin downregulates the expression of angiogenic and lymphangiogenic markers in tumor tissues. Taken together, the evidence suggested that a THP-1 macrophage and A549 cell co-culture stimulates angiogenesis and lymphangiogenesis via the NLRP3 axis. Melatonin protected against the TAMs- and NLRP3 axis-associated promotion of the aforementioned events in vitro and in vivo. Hence, melatonin is a promising candidate for managing for tumor-related angiogenesis and lymphangiogenesis in lung adenocarcinoma.

An automated commissioning method based on virtual source models: Customizing Monte Carlo dose verification models for individual accelerators.

BACKGROUND: In pursuit of precise dose calculation and verification, the importance of beam modelling cannot be overstated, as it ensures an accurate distribution of particles incident upon the human body. The virtual source model, as one of the beam modelling methods, offers the advantage of not requiring detailed accelerator information. Although various virtual source models exist, manual adjustment to these models demands a substantial investment of time and computational resources. There has long been a desire to develop an efficient and automated approach for model commissioning. PURPOSE: To develop an automatic commissioning method for the virtual source model to customize the accelerator model for independent Monte Carlo dose verification. METHODS: Initially, the accelerator model is established using the virtual source model and self-developed Jaw and MLC models. Then, a fully automated iteration process is employed to adjust the parameters of the virtual source model. Three types of objective functions are designed to represent differences from water tank measurements. Each objective function is paired with a specific parameter for adjustment, and their effectiveness is demonstrated through physical evidence. In each iteration, parameters with the highest objective function percentage are chosen for adjustment, and step length is determined based on current objective function values. Iteration is terminated when changes in any direction from the optimal solution no longer produce an improvement. Dose verification model for nine accelerators has been accomplished using this method. Additionally, under the same initial conditions, verification models for Versa HD accelerator (FF and FFF modes) are established using this method, Nelder-Mead Simplex optimization method, and the Bayesian optimization method to compare the efficiency and quality of these three iterative approaches. RESULTS: Iterations for all nine accelerators are completed within 30 iterations. The relative dose differences in dose fall-off region compared to water tank measurements are all less than 2%, and the average gamma passing rates (3%/2 mm) for ArcCHECK measurements in QA plans are all higher than 97%. For Versa HD accelerator in FFF and FF modes, the proposed method achieves an average relative dose difference below 1% within 11 and 13 iterations, respectively. In contrast, the Simplex optimization reached 1% within 78 iterations in FFF mode. Furthermore, the Simplex optimization in FF mode and Bayesian optimization in both modes failed to achieve a 1% difference within 100 iterations. CONCLUSIONS: The proposed iterative method achieves fast and automated commissioning of dose verification models, contributing to accurate and reliable clinical dose verification.

Intraoperative confocal laser endomicroscopy during 5-aminolevulinic acid-guided glioma surgery: significant considerations for resection at the tumor margin.

OBJECTIVE: Because gliomas have poorly defined tumor margins, the ability to achieve maximal resection is limited. To better discern these margins, fluorescence-guided surgery has been used to aid maximal safe resection. The authors describe their experience with the simultaneous use of intraoperative fluorescein sodium (FNa) confocal laser endomicroscopy (CLE) and operating microscope 5-aminolevulinic acid (5-ALA) fluorescence imaging for glioma resection to improve CLE use for better margin discrimination. METHODS: FNa CLE and 5-ALA wide-field imaging were used in 33 patients with gliomas. CLE imaging was enhanced with the use of a telesurgical pathology software platform that enables real-time conversation between the operating neurosurgeons and the pathologists located remotely. CLE was used for imaging tumor regions that were subjectively regarded as tumor margins under normal visualization with the operative microscope. After FNa CLE imaging, 5-ALA wide-field imaging was performed in the same regions. Tissue was biopsied at imaging locations, and interpretations of FNa CLE and 5-ALA wide-field imaging were compared to those of permanent histological sections. RESULTS: Eighty-eight deep- and superficial-margin regions of interest (ROIs) were imaged with FNa CLE and 5-ALA imaging. Most of the ROIs interpreted by the neuropathologist as infiltrative glioma based on FNa CLE imaging lacked 5-ALA-induced fluorescence. Permanent histological sections from the corresponding regions were concordant with the interpretation of FNa CLE images in 57 of 88 (65%) ROIs and with the interpretation of 5-ALA imaging in 43 of 88 (49%) ROIs. The sensitivity and specificity of FNa CLE for the interpretation of tumor margins were 73% and 41%, respectively, and those of 5-ALA were 38% and 82%, respectively. Positive and negative predictive values for CLE were 79% and 33%, respectively, and those for 5-ALA were 86% and 31%, respectively. CONCLUSIONS: Conventional intraoperative evaluation of tumor margins, based on MRI and wide-field fluorescence imaging, can underestimate the invasiveness of gliomas. FNa CLE showed higher accuracy in detecting regions with infiltrating tumors than intraoperative 5-ALA imaging. Future considerations should include more rigorous comparisons of FNa CLE imaging and 5-ALA-guided resections on a larger cohort of patients.

Dose escalation in radical radio(chemo)therapy for cervical and upper thoracic esophageal cancer with 3DCRT/IMRT (ChC&UES): a multicenter retrospective study.

BACKGROUND: Cervical and upper thoracic esophageal cancer (ESCA) presents treatment challenges due to limited clinical evidence. This multi-center study (ChC&UES) explores radical radio(chemo)therapy efficacy and safety, especially focusing on radiation dose. METHOD: We retrospectively analyzed clinical data from 1,422 cases across 8 medical centers. According to the radiation dose for primary gross tumor, patients were divided into standard dose radiotherapy (SD, 50-55 Gy) or high dose (HD, > 55 Gy) radiotherapy. HD was further subdivided into conventional- high-dose group (HD-conventional, 55-63 Gy) and ultra-high-dose group (HD-ultra, ≥ 63 Gy). Primary outcome was Overall Survival (OS). RESULTS: The median OS was 33.0 months (95% CI: 29.401-36.521) in the whole cohort. Compared with SD, HD shown significant improved survival in cervical ESCA in Kaplan-Meier (P = 0.029) and cox multivariate regression analysis (P = 0.024) while shown comparable survival in upper thoracic ESCA (P = 0.735). No significant difference existed between HD-conventional and HD-ultra in cervical (P = 0.976) and upper thoracic (P = 0.610) ESCA. Incidences of radiation esophagitis and pneumonia from HD were comparable to SD (P = 0.097, 0.240), while myosuppression risk was higher(P = 0.039). The Bonferroni method revealed that, for both cervical and upper thoracic ESCA, HD-ultra enhance the objective response rate (ORR) compared to SD (P < 0.05). CONCLUSION: HD radiotherapy benefits cervical but not upper thoracic ESCA, while increasing bone marrow suppression risk. Further dose escalating (≥ 63 Gy) doesn't improve survival but enhances ORR.

Engineering of Substrate-Binding Domain to Improve Catalytic Activity of Chondroitin B Lyase with Semi-Rational Design.

Dermatan sulfate and chondroitin sulfate are dietary supplements that can be utilized as prophylactics against thrombus formation. Low-molecular-weight dermatan sulfate (LMWDS) is particularly advantageous due to its high absorbability. The enzymatic synthesis of low-molecular-weight dermatan sulfates (LMWDSs) using chondroitin B lyase is a sustainable and environmentally friendly approach to manufacturing. However, the industrial application of chondroitin B lyases is severely hampered by their low catalytic activity. To improve the activity, a semi-rational design strategy of engineering the substrate-binding domain of chondroitin B lyase was performed based on the structure. The binding domain was subjected to screening of critical residues for modification using multiple sequence alignments and molecular docking. A total of thirteen single-point mutants were constructed and analyzed to assess their catalytic characteristics. Out of these, S90T, N103C, H134Y, and R159K exhibited noteworthy enhancements in activity. This study also examined combinatorial mutagenesis and found that the mutant H134Y/R159K exhibited a substantially enhanced catalytic activity of 1266.74 U/mg, which was 3.21-fold that of the wild-type one. Molecular docking revealed that the enhanced activity of the mutant could be attributed to the formation of new hydrogen bonds and hydrophobic interactions with the substrate as well as neighbor residues. The highly active mutant would benefit the utilization of chondroitin B lyase in pharmaceuticals and functional foods.

Surface Ammonium Ions Assisted Decoration of Monodisperse Cobalt Nanoparticles on Molybdenum Oxide Films as Efficient Electrocatalysts for Hydrogen Evolution Reaction.

The high expense associated with electrocatalysts poses a challenge to the advancement of a hydrogen-based energy economy. The utilization of nonprecious metal-based electrocatalysts that are easily prepared and cost-effective is imperative for the future sustainability of a hydrogen society. The semiconductive MoO3-x has been identified as a promising nonprecious electrocatalyst for the hydrogen evolution reaction (HER). Nevertheless, enhancing its relatively low electrocatalytic activity toward HER remains a top priority. This study illustrates the manipulation of surface ammonium ions (NH4+) to produce uniform and distinct cobalt nanoparticles (Co NPs) on active MoO3-x supports, resulting in a more effective heterostructured composite electrocatalyst for HER. The presence of NH4+ ions in the MoO3-x film was extensively examined using infrared spectroscopy, X-ray photoelectron spectroscopy, and UV-visible colorimetric techniques. Additionally, the firmly attached NH4+ ions were employed as binding sites to precipitate Co-containing complex ions. Due to the monolayer-like adsorption of NH4+ ions, only a small quantity of Co precipitate was formed, which was subsequently electrochemically transformed into Co atoms that diffused and created well-separated uniform metallic Co nanoparticles (with an average size of less than 10 nm) on the MoO3-x film. The resulting heterostructure displays a 4.5-fold increase in current density for HER compared to the MoO3-x electrocatalyst through electrochemical assessments. The enhanced catalytic activity was ascribed to the optimized adsorption/desorption of the species involved in water reduction at the heterointerfaces and improved charge transfer rates. These nanoheterostructures hold great promise for a variety of applications in heterogeneous electrocatalysis, while the novel approach could potentially direct the creation of more heterostructures.

Activation of GPR30 Ameliorates Cerebral Ischemia-Reperfusion Injury by Suppressing Ferroptosis Through Nrf2/GPX4 Signaling Pathway.

The newly identified estrogen receptor, G protein-coupled receptor 30 (GPR30), is prevalent in the brain and has been shown to provide significant neuroprotection. Recent studies have linked ferroptosis, a newly characterized form of programmed cell death, closely with cerebral ischemia-reperfusion injury (CIRI), highlighting it as a major contributing factor. Consequently, our research aimed to explore the potential of GPR30 targeting in controlling neuronal ferroptosis and lessening CIRI impacts. Results indicated that GPR30 activation not only improved neurological outcomes and decreased infarct size in a mouse model but also lessened iron accumulation and malondialdehyde formation post-middle cerebral artery occlusion (MCAO). This protective effect extended to increased levels of Nrf2 and GPX4 proteins. Similar protective results were replicated in PC12 cells subjected to Oxygen Glucose Deprivation and Reoxygenation (OGD/R) using the GPR30-specific agonist G1. Importantly, inhibition of Nrf2 with ML385 curtailed the neuroprotective effects of GPR30 activation, suggesting that GPR30 mitigates CIRI primarily through inhibition of neuronal ferroptosis via upregulation of Nrf2 and GPX4.