Prediction model and its application of helium extraction OPEX based on response surface methodology.

Focusing on the situation of the low helium content in natural gas resource in China and the high cost of helium extraction, the OPEX prediction model of helium extraction that based on the Response Surface Methodology (RSM) is proposed. This method applies ASPEN-HYSYS software to simulate the helium extraction process flow for a given product composition, pressure, and temperature; Applying the Design Expert module for Response Surface Methodology(RSM) parameter design, combined with OPEX of existing projects, determine the key influencing factors and upper and lower limits of OPEX, and obtaining the corresponding OPEX for different parameter values; Applying the Box Behnken Design (BBD) principle to optimize the helium extraction process parameters of RSM, based on fitting results and parameter significance verification of second-order regression function, the OPEX prediction model is built.This method is applied to a domestic helium extraction project, and the unit helium extraction cost is between 100 and 119.52 yuan/m3, IRR is 13.37%. The result shows the project has economic benefit, and the method presents a good perspective application.

[Effects of Land Use Patterns on Soil Microplastic Pollution in the Luoshijiang Sub-watershed of Erhai Lake Basin].

Microplastic pollution in the soil environment has received extensive attention, but the effects of different land use patterns on the sub-watershed scale on soil microplastic pollution are poorly understood. The Luoshijiang sub-watershed in the north of Erhai Lake was selected as the research object, and the characteristics of microplastic pollution in farmland, riparian zone, grassland, and woodland soils were analyzed. The pollution risks of microplastics in the four types of soil were assessed using the polymer risk index method, and the effects of land use patterns on the distribution and risk of microplastic pollution were further explored. The results showed that:① The abundance of microplastics in the soil of the Luoshijiang sub-watershed ranged from 220 to 1 900 n·kg-1, and the average abundance was (711 ± 55) n·kg-1. The main polymer types were polyester (PES, 32.52%) and polyethylene terephthalate (PET, 21.95%). The particle size of microplastics was concentrated in the range of 0.5-2 mm (61.89%). Fiber was the main shape of microplastics (>75%), and the dominant color was transparent (58.50%). ② Land use patterns determined the abundance and pollution characteristics of soil microplastics in the Luoshijiang sub-watershed. A significantly higher abundance of microplastics was found in the soil of farmland[(885 ± 95) n·kg-1] and riparian zone[(837 ± 155) n·kg-1], which had stronger intensities of human activity, than that in woodland soil[(491 ± 53) n·kg-1] (P<0.05). Film and fragment microplastics mainly occurred in farmland soil, which also had the largest number of polymer types and the most abundant colors. ③ The risk index level of microplastics (Level Ⅲ) in the soil of farmland was higher than that of the other three land use patterns (Level Ⅰ). This research indicated that the higher the intensity of human activities of a sub-watershed was, the more complex the occurrence characteristics of soil microplastics, the richer the types of polymers, and the higher the potential pollution risks would be. Therefore, it is necessary to strengthen the control of soil microplastic pollution in farmland.

Interpretable Deep Learning System for Identifying Critical Patients Through the Prediction of Triage Level, Hospitalization, and Length of Stay: Prospective Study.

BACKGROUND: Triage is the process of accurately assessing patients' symptoms and providing them with proper clinical treatment in the emergency department (ED). While many countries have developed their triage process to stratify patients' clinical severity and thus distribute medical resources, there are still some limitations of the current triage process. Since the triage level is mainly identified by experienced nurses based on a mix of subjective and objective criteria, mis-triage often occurs in the ED. It can not only cause adverse effects on patients, but also impose an undue burden on the health care delivery system. OBJECTIVE: Our study aimed to design a prediction system based on triage information, including demographics, vital signs, and chief complaints. The proposed system can not only handle heterogeneous data, including tabular data and free-text data, but also provide interpretability for better acceptance by the ED staff in the hospital. METHODS: In this study, we proposed a system comprising 3 subsystems, with each of them handling a single task, including triage level prediction, hospitalization prediction, and length of stay prediction. We used a large amount of retrospective data to pretrain the model, and then, we fine-tuned the model on a prospective data set with a golden label. The proposed deep learning framework was built with TabNet and MacBERT (Chinese version of bidirectional encoder representations from transformers [BERT]). RESULTS: The performance of our proposed model was evaluated on data collected from the National Taiwan University Hospital (901 patients were included). The model achieved promising results on the collected data set, with accuracy values of 63%, 82%, and 71% for triage level prediction, hospitalization prediction, and length of stay prediction, respectively. CONCLUSIONS: Our system improved the prediction of 3 different medical outcomes when compared with other machine learning methods. With the pretrained vital sign encoder and repretrained mask language modeling MacBERT encoder, our multimodality model can provide a deeper insight into the characteristics of electronic health records. Additionally, by providing interpretability, we believe that the proposed system can assist nursing staff and physicians in taking appropriate medical decisions.

Alginate oligosaccharide assimilation by gut microorganisms and the potential role in gut inflammation alleviation.

Dietary fiber metabolism by gut microorganisms plays important roles in host physiology and health. Alginate, the major dietary fiber of daily diet seaweeds, is drawing more attention because of multiple biological activities. To advance the understanding of alginate assimilation mechanism in the gut, we show the presence of unsaturated alginate oligosaccharides (uAOS)-specific alginate utilization loci (AUL) in human gut microbiome. As a representative example, a working model of the AUL from the gut microorganism Bacteroides clarus was reconstructed from biochemistry and transcriptome data. The fermentation of resulting monosaccharides through Entner-Doudoroff pathway tunes the metabolism of short-chain fatty acids and amino acids. Furthermore, we show that uAOS feeding protects the mice against dextran sulfate sodium-induced acute colitis probably by remodeling gut microbiota and metabolome. IMPORTANCE: Alginate has been included in traditional Chinese medicine and daily diet for centuries. Recently discovered biological activities suggested that alginate-derived alginate oligosaccharides (AOS) might be an active ingredient in traditional Chinese medicine, but how these AOS are metabolized in the gut and how it affects health need more information. The study on the working mechanism of alginate utilization loci (AUL) by the gut microorganism uncovers the role of unsaturated alginate oligosaccharides (uAOS) assimilation in tuning short-chain fatty acids and amino acids metabolism and demonstrates that uAOS metabolism by gut microorganisms results in a variation of cell metabolites, which potentially contributes to the physiology and health of gut.

ADMETlab 3.0: an updated comprehensive online ADMET prediction platform enhanced with broader coverage, improved performance, API functionality and decision support.

ADMETlab 3.0 is the second updated version of the web server that provides a comprehensive and efficient platform for evaluating ADMET-related parameters as well as physicochemical properties and medicinal chemistry characteristics involved in the drug discovery process. This new release addresses the limitations of the previous version and offers broader coverage, improved performance, API functionality, and decision support. For supporting data and endpoints, this version includes 119 features, an increase of 31 compared to the previous version. The updated number of entries is 1.5 times larger than the previous version with over 400 000 entries. ADMETlab 3.0 incorporates a multi-task DMPNN architecture coupled with molecular descriptors, a method that not only guaranteed calculation speed for each endpoint simultaneously, but also achieved a superior performance in terms of accuracy and robustness. In addition, an API has been introduced to meet the growing demand for programmatic access to large amounts of data in ADMETlab 3.0. Moreover, this version includes uncertainty estimates in the prediction results, aiding in the confident selection of candidate compounds for further studies and experiments. ADMETlab 3.0 is publicly for access without the need for registration at: https://admetlab3.scbdd.com.

Micromonospora cathayae sp. nov., isolated from the rhizosphere soil of Cathaya argyrophylla.

A novel actinobacterium, strain HUAS 3T, was isolated from the rhizosphere soil of Cathaya argyrophylla collected in Hunan Province, PR China. Strain HUAS 3T contained meso-diaminopimelic acid in the cell-wall peptidoglycan. The dominant menaquinones were MK-9(H4), MK-9(H6), MK-10(H2) and MK-9(H4). The polar lipids consisted of diphosphatidylglycerol, phospholipids, phosphatidylethanolamine, phosphatidylglycerol, phosphotidylinositol and phosphatidylinositol mannosides. The main cellular fatty acids (>5.0 %) were C17 : 1 ω8c, iso-C16 : 0, C18 : 1 ω9c, iso-C15 : 0, C16 : 0 and summed feature 3 (C16 : 1 ω6c and/or C16 : 1 ω7c). The DNA G+C content of the novel strain's genome sequence, consisting of 7 196 442 bp, was 72.8 mol%. The full-length 16S rRNA gene sequence analysis indicated that strain HUAS 3T belonged to the genus Micromonospora and showed highest similarities to Micromonospora fluminis A38T (99.44 %), Micromonospora echinospora DSM 43816T (99.23 %), Micromonospora tulbaghiae DSM 45142T (99.23 %), Micromonospora solifontis PPF5-17T (99.16 %) and Micromonospora endolithica DSM 44398T (98.96 %). Phylogenetic trees based on 16S rRNA gene sequences showed that strain HUAS 3T was closely related to M. fluminis A38T, M. tulbaghiae DSM 45142T and M. solifontis PPF5-17T. The phylogenomic tree revealed that strain HUAS 3T was closely related to Micromonospora pallida DSM 43817T. However, the average nucleotide identity (ANIb/ANIm) and the digital DNA-DNA hybridization values between them were 84.75 /88.16 and 30.80 %, respectively, far less than the 95-96 and 70 % cut-off points recommended for delineating species. Furthermore, strain HUAS 3T was distinct from the type strain of M. pallida in terms of phenotypic and chemotaxonomic characteristics. In summary, strain HUAS 3T represents a novel Micromonospora species, for which the name Micromonospora cathayae sp. nov. is proposed. The type strain is HUAS 3T (=MCCC 1K08599T=JCM 36275T).

In Situ Electrochemical Rapid Induction of Highly Active γ-NiOOH Species for Industrial Anion Exchange Membrane Water Electrolyzer.

Limited by the strong oxidation environment and sluggish reconstruction process in oxygen evolution reaction (OER), designing rapid self-reconstruction with high activity and stability electrocatalysts is crucial to promoting anion exchange membrane (AEM) water electrolyzer. Herein, trace Fe/S-modified Ni oxyhydroxide (Fe/S-NiOOH/NF) nanowires are constructed via a simple in situ electrochemical oxidation strategy based on precipitation-dissolution equilibrium. In situ characterization techniques reveal that the successful introduction of Fe and S leads to lattice disorder and boosts favorable hydroxyl capture, accelerating the formation of highly active γ-NiOOH. The Density Functional Theory (DFT) calculations have also verified that the incorporation of Fe and S optimizes the electrons redistribution and the d-band center, decreasing the energy barrier of the rate-determining step (*O→*OOH). Benefited from the unique electronic structure and intermediate adsorption, the Fe/S-NiOOH/NF catalyst only requires the overpotential of 345 mV to reach the industrial current density of 1000 mA cm-2 for 120 h. Meanwhile, assembled AEM water electrolyzer (Fe/S-NiOOH//Pt/C-60 °C) can deliver 1000 mA cm-2 at a cell voltage of 2.24 V, operating at the average energy efficiency of 71% for 100 h. In summary, this work presents a rapid self-reconstruction strategy for high-performance AEM electrocatalysts for future hydrogen economy.

Leveraging electrochemical sensors to improve efficiency of cancer detection.

Electrochemical biosensors have emerged as a promising technology for cancer detection due to their high sensitivity, rapid response, low cost, and capability for non-invasive detection. Recent advances in nanomaterials like nanoparticles, graphene, and nanowires have enhanced sensor performance to allow for cancer biomarker detection, like circulating tumor cells, nucleic acids, proteins and metabolites, at ultra-low concentrations. However, several challenges need to be addressed before electrochemical biosensors can be clinically implemented. These include improving sensor selectivity in complex biological media, device miniaturization for implantable applications, integration with data analytics, handling biomarker variability, and navigating regulatory approval. This editorial critically examines the prospects of electrochemical biosensors for efficient, low-cost and minimally invasive cancer screening. We discuss recent developments in nanotechnology, microfabrication, electronics integration, multiplexing, and machine learning that can help realize the potential of these sensors. However, significant interdisciplinary efforts among researchers, clinicians, regulators and the healthcare industry are still needed to tackle limitations in selectivity, size constraints, data interpretation, biomarker validation, toxicity and commercial translation. With committed resources and pragmatic strategies, electrochemical biosensors could enable routine early cancer detection and dramatically reduce the global cancer burden.

Predicting Elimination of Small-Molecule Drug Half-Life in Pharmacokinetics Using Ensemble and Consensus Machine Learning Methods.

Half-life is a significant pharmacokinetic parameter included in the excretion phase of absorption, distribution, metabolism, and excretion. It is one of the key factors for the successful marketing of drug candidates. Therefore, predicting half-life is of great significance in drug design. In this study, we employed eXtreme Gradient Boosting (XGboost), randomForest (RF), gradient boosting machine (GBM), and supporting vector machine (SVM) to build quantitative structure-activity relationship (QSAR) models on 3512 compounds and evaluated model performance by using root-mean-square error (RMSE), R2, and mean absolute error (MAE) metrics and interpreted features by SHapley Additive exPlanation (SHAP). Furthermore, we developed consensus models through integrating four individual models and validated their performance using a Y-randomization test and applicability domain analysis. Finally, matched molecular pair analysis was used to extract the transformation rules. Our results revealed that XGboost outperformed other individual models (RMSE = 0.176, R2 = 0.845, MAE = 0.141). The consensus model integrating all four models continued to enhance prediction performance (RMSE = 0.172, R2 = 0.856, MAE = 0.138). We evaluated the reliability, robustness, and generalization ability via Y-randomization test and applicability domain analysis. Meanwhile, we utilized SHAP to interpret features and employed matched molecular pair analysis to extract chemical transformation rules that provide suggestions for optimizing drug structure. In conclusion, we believe that the consensus model developed in this study serve as a reliable tool to evaluate half-life in drug discovery, and the chemical transformation rules concluded in this study could provide valuable suggestions in drug discovery.

GATA3 functions downstream of BRCA1 to promote DNA damage repair and suppress dedifferentiation in breast cancer.

BACKGROUND: Inadequate DNA damage repair promotes aberrant differentiation of mammary epithelial cells. Mammary luminal cell fate is mainly determined by a few transcription factors including GATA3. We previously reported that GATA3 functions downstream of BRCA1 to suppress aberrant differentiation in breast cancer. How GATA3 impacts DNA damage repair preventing aberrant cell differentiation in breast cancer remains elusive. We previously demonstrated that loss of p18, a cell cycle inhibitor, in mice induces luminal-type mammary tumors, whereas depletion of either Brca1 or Gata3 in p18 null mice leads to basal-like breast cancers (BLBCs) with activation of epithelial-mesenchymal transition (EMT). We took advantage of these mutant mice to examine the role of Gata3 as well as the interaction of Gata3 and Brca1 in DNA damage repair in mammary tumorigenesis. RESULTS: Depletion of Gata3, like that of Brca1, promoted DNA damage accumulation in breast cancer cells in vitro and in basal-like breast cancers in vivo. Reconstitution of Gata3 improved DNA damage repair in Brca1-deficient mammary tumorigenesis. Overexpression of GATA3 promoted homologous recombination (HR)-mediated DNA damage repair and restored HR efficiency of BRCA1-deficient cells. Depletion of Gata3 sensitized tumor cells to PARP inhibitor (PARPi), and reconstitution of Gata3 enhanced resistance of Brca1-deficient tumor cells to PARP inhibitor. CONCLUSIONS: These results demonstrate that Gata3 functions downstream of BRCA1 to promote DNA damage repair and suppress dedifferentiation in mammary tumorigenesis and progression. Our findings suggest that PARP inhibitors are effective for the treatment of GATA3-deficient BLBCs.

Mitofilin in cardiovascular diseases: Insights into the pathogenesis and potential pharmacological interventions.

The impact of mitochondrial dysfunction on the pathogenesis of cardiovascular disease is increasing. However, the precise underlying mechanism remains unclear. Mitochondria produce cellular energy through oxidative phosphorylation while regulating calcium homeostasis, cellular respiration, and the production of biosynthetic chemicals. Nevertheless, problems related to cardiac energy metabolism, defective mitochondrial proteins, mitophagy, and structural changes in mitochondrial membranes can cause cardiovascular diseases via mitochondrial dysfunction. Mitofilin is a critical inner mitochondrial membrane protein that maintains cristae structure and facilitates protein transport while linking the inner mitochondrial membrane, outer mitochondrial membrane, and mitochondrial DNA transcription. Researchers believe that mitofilin may be a therapeutic target for treating cardiovascular diseases, particularly cardiac mitochondrial dysfunctions. In this review, we highlight current findings regarding the role of mitofilin in the pathogenesis of cardiovascular diseases and potential therapeutic compounds targeting mitofilin.

Innovations in WO3 gas sensors: Nanostructure engineering, functionalization, and future perspectives.

This review critically examines the progress and challenges in the field of nanostructured tungsten oxide (WO3) gas sensors. It delves into the significant advancements achieved through nanostructuring and composite formation of WO3, which have markedly improved sensor sensitivity for gases like NO2, NH3, and VOCs, achieving detection limits in the ppb range. The review systematically explores various innovative approaches, such as doping WO3 with transition metals, creating heterojunctions with materials like CuO and graphene, and employing machine learning models to optimize sensor configurations. The challenges facing WO3 sensors are also thoroughly examined. Key issues include cross-sensitivity to different gases, particularly at higher temperatures, and long-term stability affected by factors like grain growth and volatility of dopants. The review assesses potential solutions to these challenges, including statistical analysis of sensor arrays, surface functionalization, and the use of novel nanostructures for enhanced performance and selectivity. In addition, the review discusses the impact of ambient humidity on sensor performance and the current strategies to mitigate it, such as composite materials with humidity shielding effects and surface functionalization with hydrophobic groups. The need for high operating temperatures, leading to higher power consumption, is also addressed, along with possible solutions like the use of advanced materials and new transduction principles to lower temperature requirements. The review concludes by highlighting the necessity for a multidisciplinary approach in future research. This approach should combine materials synthesis, device engineering, and data science to develop the next generation of WO3 sensors with enhanced sensitivity, ultrafast response rates, and improved portability. The integration of machine learning and IoT connectivity is posited as a key driver for new applications in areas like personal exposure monitoring, wearable diagnostics, and smart city networks, underlining WO3's potential as a robust gas sensing material in future technological advancements.

NUS1 Variants Cause Lennox-Gastaut Syndrome Related to Unfolded Protein Reaction Activation.

NUS1 encodes the Nogo-B receptor, a critical regulator for unfolded protein reaction (UPR) signaling. Although several loss-of-function variants of NUS1 have been identified in patients with developmental and epileptic encephalopathy (DEE), the role of the NUS1 variant in Lennox-Gastaut syndrome (LGS), a severe child-onset DEE, remains unknown. In this study, we identified two de novo variants of NUS1, a missense variant (c.868 C > T/p.R290C) and a splice site variant (c.792-2 A > G), in two unrelated LGS patients using trio-based whole-exome sequencing performed in a cohort of 165 LGS patients. Both variants were absent in the gnomAD population and showed a significantly higher observed number of variants than expected genome-wide. The R290C variant was predicted to damage NUS1 and decrease its protein stability. The c.792-2 A > G variant caused premature termination of the protein. Knockdown of NUS1 activated the UPR pathway, resulting in apoptosis of HEK293T cells. Supplementing cells with expression of wild-type NUS1, but not the mutant (R290C), rescued UPR activation and apoptosis in NUS1 knockdown cells. Compared to wild-type Drosophila, seizure-like behaviors and excitability in projection neurons were significantly increased in Tango14 (homolog of human NUS1) knockdown and Tango14R290C/+ knock-in Drosophila. Additionally, abnormal development and a small body size were observed in both mutants. Activated UPR signaling was also detected in both mutants. Thus, NUS1 is a causative gene for LGS with dominant inheritance. The pathogenicity of these variants is related to the UPR signaling activation, which may be a common pathogenic mechanism of DEE.

Evaluating the effects of circulating inflammatory proteins as drivers and therapeutic targets for severe COVID-19.

Objective: The relationships between circulating inflammatory proteins and COVID-19 have been observed in previous cohorts. However, it is not unclear which circulating inflammatory proteins may boost the risk of or protect against COVID-19. Methods: We performed Mendelian randomization (MR) analysis using GWAS summary result of 91 circulating inflammation-related proteins (N = 14,824) to assess their causal impact on severe COVID-19. The COVID-19 phenotypes encompassed both hospitalized (N = 2,095,324) and critical COVID-19 (N = 1,086,211). Moreover, sensitivity analyses were conducted to evaluate the robustness and reliability. Results: We found that seven circulating inflammatory proteins confer positive causal effects on severe COVID-19. Among them, serum levels of IL-10RB, FGF-19, and CCL-2 positively contributed to both hospitalized and critical COVID-19 conditions (OR: 1.10~1.16), while the other 4 proteins conferred risk on critical COVID-19 only (OR: 1.07~1.16), including EIF4EBP1, IL-7, NTF3, and LIF. Meanwhile, five proteins exert protective effects against hospitalization and progression to critical COVID-19 (OR: 0.85~0.95), including CXCL11, CDCP1, CCL4/MIP, IFNG, and LIFR. Sensitivity analyses did not support the presence of heterogeneity in the majority of MR analyses. Conclusions: Our study revealed risk and protective inflammatory proteins for severe COVID-19, which may have vital implications for the treatment of the disease.

Extending the Grading of Recommendations Assessment, Development and Evaluation (GRADE) in Traditional Chinese Medicine (TCM): The GRADE-TCM.

AIM: To extend and form the "Grading of Recommendations Assessment, Development and Evaluation in Traditional Chinese Medicine" (GRADE-TCM). METHODS: Methodologies were systematically reviewed and analyzed concerning evidence-based TCM guidelines worldwide. A survey questionnaire was developed based on the literature review and open-end expert interviews. Then, we performed expert consensus, discussion meeting, opinion collection, external examination, and the GRADE-TCM was formed eventually. RESULTS: 265 Chinese and English TCM guidelines were included and analyzed. Five experts completed the open-end interviews. Ten methodological entries were summarized, screened and selected. One round of consensus was conducted, including a total of 22 experts and 220 valid questionnaire entries, concerning 1) selection of the GRADE, 2) GRADE-TCM upgrading criteria, 3) GRADE-TCM evaluation standard, 4) principles of consensus and recommendation, and 5) presentation of the GRADE-TCM and recommendation. Finally, consensus was reached on the above 10 entries, and the results were of high importance (with voting percentages ranging from 50 % to 81.82 % for "very important" rating) and strong reliability (with the Cr ranging from 0.93 to 0.99). Expert discussion meeting (with 40 experts), opinion collection (in two online platforms) and external examination (with 14 third-party experts) were conducted, and the GRADE-TCM was established eventually. CONCLUSION: GRADE-TCM provides a new extended evidence-based evaluation standard for TCM guidelines. In GRADE-TCM, international evidence-based norms, characteristics of TCM intervention, and inheritance of TCM culture were combined organically and followed. This is helpful for localization of the GRADE in TCM and internationalization of TCM guidelines.

Mutational landscape of TP53 and CDH1 in gastric cancer.

In this editorial we comment on an article published in a recent issue of the World J Gastrointest Surg. A common gene mutation in gastric cancer (GC) is the TP53 mutation. As a tumor suppressor gene, TP53 is implicated in more than half of all tumor occurrences. TP53 gene mutations in GC tissue may be related with clinical pathological aspects. The TP53 mutation arose late in the progression of GC and aided in the final switch to malignancy. CDH1 encodes E-cadherin, which is involved in cell-to-cell adhesion, epithelial structure maintenance, cell polarity, differentiation, and intracellular signaling pathway modulation. CDH1 mutations and functional loss can result in diffuse GC, and CDH1 mutations can serve as independent prognostic indicators for poor prognosis. GC patients can benefit from genetic counseling and testing for CDH1 mutations. Demethylation therapy may assist to postpone the onset and progression of GC. The investigation of TP53 and CDH1 gene mutations in GC allows for the investigation of the relationship between these two gene mutations, as well as providing some basis for evaluating the prognosis of GC patients.

Geometric lightguide for near-eye light field displays.

Most near-eye displays with one fixed focal plane suffer from the vergence-accommodation conflict and cause visual discomfort to users. In contrast, light field displays can provide natural and comfortable 3D visual sensation to users without the conflict. This paper presents a near-eye light field display consisting of a geometric lightguide and a light field generator, along with a collimator to ensure the light rays propagating in the lightguide are collimated. Unlike most lightguides, which reduce thickness by employing total internal reflection that can easily generate stray light, our lightguide directly propagates light rays without total internal reflection. The partially reflective mirrors of the lightguide expand the exit pupil to achieve an eyebox of 13m m(h o r i z o n t a l)×6.5m m(v e r t i c a l) with an eye relief of 18 mm. The collimator and the light field generator, both having effective focal lengths different in the horizontal and vertical directions, are designed to provide a 40-deg diagonal field of view. The working range of the light field generator, which is 30 cm to infinity, is verified qualitatively and quantitatively by experiments. We optimize the illuminance uniformity and analyze the illuminance variation across the eyebox. Further, we minimize the ghost artifact (referring to the split-up of light fields replicated by the partially reflective mirrors) by orienting the partially reflective mirrors at slightly different angles to enhance the image quality for short-range applications such as medical surgery.

Cutaneous Melanoma and 486 Human Blood Metabolites: A Mendelian Randomization Study.

BACKGROUND: Cutaneous melanoma (CM) has long been recognized as a lethal form of cancer. Despite persistent research endeavors, the precise underlying pathological mechanisms remain largely unclear, and the optimal treatment for this patient population remains undetermined. OBJECTIVES: This study aims to examine the causal associations between CM and 486 metabolites. METHODS: A two-sample Mendelian randomization (MR) analysis was conducted to ascertain the causal relationship between blood metabolites and CM. The causality analysis involved the inverse variance weighted (IVW) method, followed by the MR-Egger and weighted median (WM) methods. To increase the robustness of our findings, several sensitivity analyses, including the MR-Egger intercept, Cochran's Q test, and MR-pleiotropy residual sum and outlier (MR-PRESSO), were performed. The robustness of our results was further validated in independent outcome samples followed by a meta-analysis. Additionally, a metabolic pathway analysis was carried out. RESULTS: The two-sample MR analysis yielded a total of 27 metabolites as potential causal metabolites. After incorporating the outcomes of the sensitivity analyses, seven causal metabolites remained. Palmitoylcarnitine (OR 0.9903 95% CI 0.9848-0.9958, p = 0.0005) emerged as the sole metabolite with a significant causality after Bonferroni correction. Furthermore, the reverse MR analysis provided no evidence of reverse causality from CM to the identified metabolites. CONCLUSIONS: This study suggested a causal relationship between seven human blood metabolites and the development of CM, thereby offering novel insights into the underlying mechanisms involved. NO LEVEL ASSIGNED: This journal requires that authors assign a level of evidence to each submission to which Evidence-Based Medicine rankings are applicable. This excludes Review Articles, Book Reviews, and manuscripts that concern Basic Science, Animal Studies, Cadaver Studies, and Experimental Studies. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Tuning Electrocatalytic Water Oxidation Activity: Insights from the Active-Site Distance in LnCu6 Clusters.

Atomically precise metal clusters serve as a unique model for unraveling the intricate mechanism of the catalytic reaction and exploring the complex relationship between structure and activity. Herein, three series of water-soluble heterometallic clusters LnCu6, abbreviated as LnCu6-AC (Ln = La, Nd, Gd, Er, Yb; HAC = acetic acid), LnCu6-IM (Ln = La and Nd; IM = Imidazole), and LnCu6-IDA (Ln = Nd; H2IDA = Iminodiacetic acid) are presented, each featuring a uniform metallic core stabilized by distinct protected ligands. Crystal structure analysis reveals a triangular prism topology formed by six Cu2+ ions around one Ln3+ ion in LnCu6, with variations in Cu···Cu distances attributed to different ligands. Electrocatalytic oxygen evolution reaction (OER) shows that these different LnCu6 clusters exhibit different OER activities with remarkable turnover frequency of 135 s-1 for NdCu6-AC, 79 s-1 for NdCu6-IM and 32 s-1 for NdCu6-IDA. Structural analysis and Density Functional Theory (DFT) calculations underscore the correlation between shorter Cu···Cu distances and improves OER catalytic activity, emphasizing the pivotal role of active-site distance in regulating electrocatalytic OER activities. These results provide valuable insights into the OER mechanism and contribute to the design of efficient homogeneous OER electrocatalysts.

Evaluating the efficacy of balloon pulmonary angioplasty using quantitative analysis of SPECT pulmonary ventilation/perfusion scintigraphy in patients with chronic thromboembolic pulmonary hypertension.

Background: Single-photon emission computed tomography (SPECT) ventilation perfusion imaging is the main imaging method for the diagnosis of pulmonary embolism, and its application in the diagnosis and efficacy evaluation of chronic thromboembolic pulmonary hypertension (CTEPH) has been paid more and more attention. In recent years, with the development of computer software technology, ventilation/perfusion (V/Q) imaging quantitative analysis technology has become more and more mature. The objective of this study was to investigate the utility of quantitative analysis of pulmonary V/Q scintigraphy in evaluating the efficacy of balloon pulmonary angioplasty (BPA) in patients with CTEPH. Methods: In this retrospective analysis, we collected data of patients diagnosed with CTEPH who underwent BPA at the China-Japan Friendship Hospital from April 2018 to September 2020. The sample consisted of 23 males and 28 females, with an average age of 55.1±12.7 years. All patients underwent V/Q scintigraphy within one week before surgery, and we reviewed the pulmonary angiography within 1-3 months following the last BPA procedure. We repeated V/Q scintigraphy within 1 week before or after the pulmonary angiography, at the time of collecting clinical and hemodynamic parameters of these patients. We divided the patients into two groups based on the presence of residual pulmonary hypertension post-surgery and compared the pre- and post-operative quantitative pulmonary perfusion defect percentage scores (PPDs%) using the t-test. Results: In all, 102 V/Q scintigraphy scans were performed in 51 patients. The quantitative PPDs% were positively correlated with the hemodynamic indexes mean pulmonary arterial pressure (mPAP), pulmonary vascular resistance (PVR), and mean right ventricular pressure (RVP) (r=0.605, 0.391, and 0.464, respectively, all P<0.001) and negatively correlated with the 6-minute walking distance (6MWD) (r=-0.254, P=0.010). The average preoperative quantitative PPDs% were (49.0±15.6)% which significantly decreased to (33.5±13.9)% after surgery (t=11.249, P<0.001). The preoperative quantitative PPDs% were (54.7±15.7)% and (44.0±13.8)% in the residual pulmonary hypertension group and the non-residual pulmonary hypertension group, respectively (t=2.599, P=0.012). The postoperative quantitative PPDs% were (41.5±12.5)% and (26.3±11.0)%, in the residual pulmonary hypertension group and the non-residual pulmonary hypertension group, respectively (t=4.647, P<0.001). Conclusions: In this study, we found that quantitative analysis of SPECT pulmonary V/Q scintigraphy adequately reflected the pulmonary artery pressure and clinical status in patients with CTEPH. Our results demonstrate its definite utility in predicting residual pulmonary hypertension and in evaluating the postoperative efficacy of BPA in patients with CTEPH.