A practical approach for extracting the photosystem II (PSII) contribution to near-infrared solar-induced chlorophyll fluorescence.

Recent studies have indicated a good potential for using solar-induced chlorophyll fluorescence (SIF) to estimate photosynthetic CO2 assimilation. SIF can be emitted by both Photosystem I (PSI) and Photosystem II (PSII), but it is the SIF signals from PSII which are related to photosynthetic carbon fixation. However, since top-of-canopy SIF observations (SIFTOC) always contain contributions from both photosystems, to mechanistically estimate gross primary productivity (GPP) from SIF, it is essential to extract PSII SIF from SIFTOC. Based on the differences in the relative contribution of PSII across different wavelengths, we propose a practical approach for extracting PSII contribution to SIFTOC at the near-infrared (NIR) band (fPSII_760) using measurements of SIFTOC in the red and NIR spectral regions. A leaf-scale concurrent instrument was developed to assess the response of fPSII_760 under varying environments. For winter-wheat leaves, as light intensity increased from 0 to 400 µmol m-2 s-1, fPSII_760 rose from 0.6 to 0.8; with further increase in light intensity to 1800 µmol m-2 s-1, fPSII_760 consistently decreased to 0.65. There was a slight decreasing trend in fPSII_760 with rising temperatures, with values dropping from 0.65 at 15 °C to 0.61 at 40 °C. We found that variations in fPSII_760 are due to changes in the fluorescence yield of PSII, with the two having a positively proportional relationship. We also estimated canopy-scale fPSII_760 for a winter-wheat study site: fPSII_760 varied from 0.61 to 0.83, with a mean value of 0.78 during the peak growing season. A comparison with eddy covariance-derived GPP reveals that GPP estimated with dynamic fPSII_760 was more accurate than that calculated using fixed fPSII_760, with R2 increasing from 0.6 to 0.84. This study contributes to a deeper understanding of the link between SIF and photosynthetic CO2 assimilation, paving the way for more effective use of SIF to estimate GPP.

A lysosome-located and rhodamine-based fluorescence probe for recognizing hydrogen polysulfide.

Hydrogen polysulfide (H2Sn, n≥2), as a kind of active sulfur species (RSS), has become a hot topic in RSS. It can regulate the biological activity of many proteins through S-sulfhydrylation of cysteine residues (protein Cys-SSH), and has a protective effect on cells. Although there have been some studies on hydrogen polysulfide, its production, degradation pathway and regulation mechanism still need further be researched. In presented study, an original lysosome-localized fluorescent probe for determining H2Sn was developed utilizing rhodamine as the fluorogen. The probe used morpholine as the locating unit of lysosomes and chose 2-fluoro-5-nitrobenzoate as the recognizing group. Before adding H2Sn, the proposed probe displayed a spironolactone structure and emitted very weak fluorescence. After adding H2Sn, a conjugated xanthene was formed and the probe demonstrated green fluorescence. When the H2Sn concentration was varied from 6.0×10-7 mol·L-1 to 10.0×10-5 mol·L-1, the fluorescence intensity of the probe was linearly dependent on the H2Sn concentration. And the detection limit was 1.5×10-7 mol·L-1. The presented probe owned a fast response speed, good selectivity, excellent sensitivity and broad pH work scope. In addition, the probe had been well utilized to sense endogenic and exogenic H2Sn in lysosomes.

Accurate EVSI Estimation for Nonlinear Models Using the Gaussian Approximation Method.

BACKGROUND: The expected value of sample information (EVSI) measures the expected benefits that could be obtained by collecting additional data. Estimating EVSI using the traditional nested Monte Carlo method is computationally expensive, but the recently developed Gaussian approximation (GA) approach can efficiently estimate EVSI across different sample sizes. However, the conventional GA may result in biased EVSI estimates if the decision models are highly nonlinear. This bias may lead to suboptimal study designs when GA is used to optimize the value of different studies. Therefore, we extend the conventional GA approach to improve its performance for nonlinear decision models. METHODS: Our method provides accurate EVSI estimates by approximating the conditional expectation of the benefit based on 2 steps. First, a Taylor series approximation is applied to estimate the conditional expectation of the benefit as a function of the conditional moments of the parameters of interest using a spline, which is fitted to the samples of the parameters and the corresponding benefits. Next, the conditional moments of parameters are approximated by the conventional GA and Fisher information. The proposed approach is applied to several data collection exercises involving non-Gaussian parameters and nonlinear decision models. Its performance is compared with the nested Monte Carlo method, the conventional GA approach, and the nonparametric regression-based method for EVSI calculation. RESULTS: The proposed approach provides accurate EVSI estimates across different sample sizes when the parameters of interest are non-Gaussian and the decision models are nonlinear. The computational cost of the proposed method is similar to that of other novel methods. CONCLUSIONS: The proposed approach can estimate EVSI across sample sizes accurately and efficiently, which may support researchers in determining an economically optimal study design using EVSI. HIGHLIGHTS: The Gaussian approximation method efficiently estimates the expected value of sample information (EVSI) for clinical trials with varying sample sizes, but it may introduce bias when health economic models have a nonlinear structure.We introduce the spline-based Taylor series approximation method and combine it with the original Gaussian approximation to correct the nonlinearity-induced bias in EVSI estimation.Our approach can provide more precise EVSI estimates for complex decision models without sacrificing computational efficiency, which can enhance the resource allocation strategies from the cost-effective perspective.

Novel prognostic biomarkers in nasopharyngeal carcinoma unveiled by mega-data bioinformatics analysis.

Nasopharyngeal carcinoma (NPC) is commonly diagnosed at an advanced stage with a high incidence rate in Southeast Asia and Southeast China. However, the limited availability of NPC patient survival data in public databases has resulted in less rigorous studies examining the prediction of NPC survival through construction of Kaplan-Meier curves. These studies have primarily relied on small samples of NPC patients with progression-free survival (PFS) information or data from head and neck squamous cell carcinoma (HNSCC) studies almost without NPC patients. Thus, we coanalyzed RNA expression profiles in eleven datasets (46 normal (control) vs 160 tumor (NPC)) downloaded from the Gene Expression Omnibus (GEO) database and survival data provided by Jun Ma from Sun Yat-sen University. Then, differential analysis, gene ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and network analysis were performed using STRING database. After that, 2142 upregulated differentially expressed genes (DEGs) and 3857 downregulated DEGs were screened. Twenty-five of them were identified as hub genes, which were enriched in several pathways (cilium movement, extracellular matrix structural constituent, homologous recombination and cell cycle). Utilizing the comprehensive dataset we amassed from GEO database, we conducted a survival analysis of DEGs and subsequently constructed survival models. Seven DEGs (RASGRP2, MOCOS, TTC9, ARHGAP4, DPM3, CD37, and CD72) were identified and closely related to the survival prognosis of NPC. Finally, qRT-PCR, WB and IHC were performed to confirm the elevated expression of RASGRP2 and the decreased expression of TTC9, CD37, DPM3 and ARHGAP4, consistent with the DEG analysis. Conclusively, our findings provide insights into the novel prognostic biomarkers of NPC by mega-data bioinformatics analysis, which suggests that they may serve special targets in the treatment of NPC.

A rhodamine-based fluorescent probe used to determine nitroxyl (HNO) in lysosomes.

The reactive nitrogen species (RNS) in lysosomes play a major role during the regulation of lysosomal microenvironment. Nitroxyl (HNO) belongs to active nitrogen species (RNS) and is becoming a potential diagnostic and therapeutic biomarker. However, the complex synthesis routes of HNO in biosystem always hinder the exact determination of HNO in living cells. Here, a rhodamine-based fluorescent probe used to determine nitroxyl (HNO) in lysosomes was constructed and synthesized. 2-(Diphenylphosphino)benzoate was utilized as the sensing unit for HNO and morpholine was chose as the targeting group for lysosome. Before the addition of HNO, the probe displayed a spirolactone structure and almost no fluorescence was found. After the addition of HNO, the probe existed as a conjugated xanthene form and an intense green fluorescence was observed. The fluorescent probe possessed fast response (3 min) and high selectivity for HNO. Furthermore, fluorescence intensity of the probe linearly related with the HNO concentration in the range of 6.0 × 10-8 to 6.0 × 10-5 mol L-1. The detection limit was found to be 1.87 × 10-8 mol L-1 for HNO. Moreover, the probe could selectively targeted lysosome with excellent biocompatibility and had been effectually utilized to recognize exogenous HNO in A549 cells.

Electrocatalytic Nitrate Reduction on Metallic CoNi-Terminated Catalyst with Industrial-Level Current Density in Neutral Medium.

Green ammonia synthesis through electrocatalytic nitrate reduction reaction (eNO3RR) can serve as an effective alternative to the traditional energy-intensive Haber-Bosch process. However, achieving high Faradaic efficiency (FE) at industrially relevant current density in neutral medium poses significant challenges in eNO3RR. Herein, with the guidance of theoretical calculation, a metallic CoNi-terminated catalyst is successfully designed and constructed on copper foam, which achieves an ammonia FE of up to 100% under industrial-level current density and very low overpotential (-0.15 V versus reversible hydrogen electrode) in a neutral medium. Multiple characterization results have confirmed that the maintained metal atom-terminated surface through interaction with copper atoms plays a crucial role in reducing overpotential and achieving high current density. By constructing a homemade gas stripping and absorption device, the complete conversion process for high-purity ammonium nitrate products is demonstrated, displaying the potential for practical application. This work suggests a sustainable and promising process toward directly converting nitrate-containing pollutant solutions into practical nitrogen fertilizers.

Systemic Immune-Inflammation Index and Systemic Inflammation Response Index are Associated With Periodontitis: Evidence From NHANES 2009 to 2014.

INTRODUCTION AND AIMS: Periodontitis, a chronic inflammatory condition affecting the supporting structures of the teeth, is a substantial public health burrden whilst impacting the life quality of those affected. Elevated levels of systemic immune-inflammation index (SII) and systemic inflammation response index (SIRI) have been implicated in various inflammatory conditions. This study aimed to investigate the relationship between SII and SIRI with periodontitis. METHODS: The study examined a total of 8666 participants in the 2009 to 2014 National Health and Nutrition Examination Survey (NHANES). The study compared the weighted prevalence of periodontitis among various groups. The association between SII, SIRI levels, and periodontitis was analyzed using binary logistic regression. Additionally, we explored nonlinear relationships between SII, SIRI, and the prevalence of periodontitis using restricted cubic spline (RCS) plots. RESULTS: Among participants in the fourth quartile (Q4) of SII and SIRI, the highest prevalence of periodontitis was observed, with rates of 44.87% and 48.41%, respectively. After adjusting for all covariates, the odds ratio (OR) for periodontitis associated with SII Q4 was 1.19 (95% CI 1.02, 1.39, P = .03), while for SIRI Q4, it was 1.18 (95% CI 1.01, 1.39, P = .04). In addition, the results of sensitivity analysis revealed consistent findings, indicating that after adjusting for all covariates, the OR for periodontitis associated with SII Q4 and SIRI Q4 remained statistically significant. Specifically, the OR for periodontitis associated with SII Q4 was 1.19 (95% CI 1.02, 1.39, P = .03), while for SIRI Q4, it was 1.19 (95% CI 1.01, 1.40, P = .04). CONCLUSIONS: These results indicate that elevated SII and SIRI levels are associated with an increased prevalence of periodontitis. CLINICAL RELEVANCE: These findings suggest a potential connection between systemic inflammation and periodontitis, highlighting the importance of periodontitis patients being aware of their systemic diseases that are inflammatory in nature such as chronic cardiovascular afflictions.

Corrigendum: Roles of ubiquitin-specific proteases in inflammatory diseases.

[This corrects the article DOI: 10.3389/fimmu.2024.1258740.].

Roles of ubiquitin-specific proteases in inflammatory diseases.

Ubiquitin-specific proteases (USPs), as one of the deubiquitinating enzymes (DUBs) families, regulate the fate of proteins and signaling pathway transduction by removing ubiquitin chains from the target proteins. USPs are essential for the modulation of a variety of physiological processes, such as DNA repair, cell metabolism and differentiation, epigenetic modulations as well as protein stability. Recently, extensive research has demonstrated that USPs exert a significant impact on innate and adaptive immune reactions, metabolic syndromes, inflammatory disorders, and infection via post-translational modification processes. This review summarizes the important roles of the USPs in the onset and progression of inflammatory diseases, including periodontitis, pneumonia, atherosclerosis, inflammatory bowel disease, sepsis, hepatitis, diabetes, and obesity. Moreover, we highlight a comprehensive overview of the pathogenesis of USPs in these inflammatory diseases as well as post-translational modifications in the inflammatory responses and pave the way for future prospect of targeted therapies in these inflammatory diseases.

Advancements and future prospects of adeno-associated virus-mediated gene therapy for sensorineural hearing loss.

Sensorineural hearing loss (SNHL), a highly prevalent sensory impairment, results from a multifaceted interaction of genetic and environmental factors. As we continually gain insights into the molecular basis of auditory development and the growing compendium of deafness genes identified, research on gene therapy for SNHL has significantly deepened. Adeno-associated virus (AAV), considered a relatively secure vector for gene therapy in clinical trials, can deliver various transgenes based on gene therapy strategies such as gene replacement, gene silencing, gene editing, or gene addition to alleviate diverse types of SNHL. This review delved into the preclinical advances in AAV-based gene therapy for SNHL, spanning hereditary and acquired types. Particular focus is placed on the dual-AAV construction method and its application, the vector delivery route of mouse inner ear models (local, systemic, fetal, and cerebrospinal fluid administration), and the significant considerations in transforming from AAV-based animal model inner ear gene therapy to clinical implementation.

Molecular diagnosis, clinical evaluation and phenotypic spectrum of Townes-Brocks syndrome: insights from a large Chinese hearing loss cohort.

BACKGROUND: Townes-Brocks syndrome (TBS) is a rare genetic disorder characterised by multiple malformations. Due to its phenotypic heterogeneity and rarity, diagnosis and recognition of TBS can be challenging and there has been a lack of investigation of patients with atypical TBS in large cohorts and delineation of their phenotypic characteristics. METHODS: We screened SALL1 and DACT1 variants using next-generation sequencing in the China Deafness Genetics Consortium (CDGC) cohort enrolling 20 666 unrelated hearing loss (HL) cases. Comprehensive clinical evaluations were conducted on seven members from a three-generation TBS family. Combining data from previously reported cases, we also provided a landscape of phenotypes and genotypes of patients with TBS. RESULTS: We identified five novel and two reported pathogenic/likely pathogenic (P/LP) SALL1 variants from seven families. Audiological features in patients differed in severity and binaural asymmetry. Moreover, previously undocumented malformations in the middle and inner ear were detected in one patient. By comprehensive clinical evaluations, we further provide evidence for the causal relationship between SALL1 variation and certain endocrine abnormalities. Penetrance analysis within familial contexts revealed incomplete penetrance among first-generation patients with TBS and a higher disease burden among their affected offspring. CONCLUSION: This study presents the first insight of genetic screening for patients with TBS in a large HL cohort. We broadened the phenotypic-genotypic spectrum of TBS and our results supported an underestimated prevalence of TBS. Due to the rarity and phenotypic heterogeneity of rare diseases, broader spectrum molecular tests, especially whole genome sequencing, can improve the situation of underdiagnosis and provide effective recommendations for clinical management.