Standard Parameters Research Articles

Combining pre- and post-recombination new physics to address cosmological tensions: Case study with varying electron mass and sign-switching cosmological constant

It has recently been argued that the Hubble tension may call for a combination of both pre- and post-recombination new physics. Motivated by these considerations, we provide one of the first concrete case studies aimed at constructing such a viable combination. We consider models that have individually worked best on either end of recombination so far: a spatially uniform time-varying electron mass leading to earlier recombination (also adding non-zero spatial curvature), and a sign-switching cosmological constant inducing an AdS-to-dS transition within the ΛsCDM model. When confronted against Cosmic Microwave Background (CMB), Baryon Acoustic Oscillations, and Type Ia Supernovae data, we show that no combination of these ingredients can successfully solve the Hubble tension. We find that the matter density parameter Ωm plays a critical role, driving important physical scales in opposite directions: the AdS-to-dS transition requires a larger Ωm to maintain the CMB acoustic scale fixed, whereas the varying electron mass requires a smaller Ωm to maintain the redshift of matter-radiation equality fixed. Despite the overall failure, we use our results to draw general model-building lessons, highlighting the importance of assessing tension-solving directions in the parameter space of new physics parameters and how these correlate with shifts in other standard parameters, while underscoring the crucial role of Ωm in this sense.

DFT and Model Hamiltonian Study of Optoelectronic Properties of Some Low-Symmetry Graphene Quantum Dots.

We have studied the electronic and optical properties of three low-symmetry graphene quantum dots (GQDs), with point-group symmetries C2v and C2h. For the calculations of linear optical absorption spectra, we employed both first-principles time-dependent density-functional theory (TDDFT) and the electron-correlated Pariser-Parr-Pople (PPP) model coupled with the configuration-interaction (CI) approach. In the PPP-CI approach, calculations were performed using both screened and standard parameters, along with efficiently incorporating electron correlation effects using multireference singles-doubles CI for both ground and excited states. We assume that the GQDs are saturated by hydrogen atoms at the edges, making them effectively polycyclic aromatic hydrocarbons (PAHs) dibenzo[bc,ef]coronene (also known as benzo(1,14)bisanthene, C30H14) and two isomeric compounds, dinaphtho[8,1,2abc;2',1',8'klm]coronene and dinaphtho[8,1,2abc;2',1',8'jkl]coronene with the chemical formula C36H16. The two isomers have different point group symmetries; therefore, this study will also help us understand the influence of symmetry on the optical properties. A common feature of the absorption spectra of the three GQDs is that the first peak representing the optical gap is of low to moderate intensity, while the intense peaks appear at higher energies. For each GQD, PPP model calculations performed with the screened parameters agree well with the experimental results of the corresponding PAH and also with the TDDFT calculations. To further quantify the influence of electron-correlation effects, we also computed the singlet-triplet gap (spin gap) of the three GQDs, and we found them to be significant.

Abstract B059: Assessment of ctDNA analysis methods using high purity ctDNA from the aqueous humor of retinoblastoma eyes

Abstract Background: Whole-genome sequencing (WGS) of cell-free DNA (cfDNA) paired with methods like ichorCNA and DELFI has become a valuable approach for detecting circulating tumor DNA (ctDNA). However, the mixture of ctDNA with non-tumor cfDNA in plasma complicates accurate validation of ctDNA detection methods. In contrast, aqueous humor (AH) from treatment-free retinoblastoma (RB) eyes is uniquely enriched in ctDNA, providing an optimal source for generating reference samples. This study leverages AH-derived biological ctDNA to evaluate two established ctDNA analysis methods. Methods: Biologically derived cfDNA mixtures were created by combining WGS reads from two AH samples with pooled reads from non-tumor blood samples (N=20). One AH sample (RB_023_OS) showed >99% tumor fraction (TFx) with ichorCNA, while the other (RB_025_OD) had confirmed presence of ctDNA based on >99% variant allele frequency (VAF) for an RB1 variant, despite being somatic copy number alteration (SCNA)-negative. Mixtures were prepared across a range of TFx values (0.01-0.5) and unique sequencing coverages (0.1x, 0.5x, 1x, and 2x). TFx was calculated using ichorCNA with standard parameters and optimized parameters for low TFx levels. We also tested an enrichment strategy targeting shorter ctDNA fragments (≤150 base pairs) and generated genome-wide fragmentation profiles using the DELFI method to assess short-to-long (S:L) fragment ratios across 5-Mb bins. Results: We evaluated the impact of sequencing coverage, parameter selection, and fragment size selection on TFx estimation by ichorCNA. Standard ichorCNA parameters demonstrated limited sensitivity, detecting ctDNA only in samples with TFx of 5-6% or higher. Increasing sequencing coverage did not substantially improve the limit of detection (LoD) or the accuracy of TFx quantification. Optimized parameters reduced the LoD to 3% TFx, but only in samples with ≥0.5x coverage, indicating a dependence on sequencing depth for accurate ctDNA detection and quantification. In RB_025_OD, where no SCNAs were present, ichorCNA failed to estimate the TFx despite an RB1 VAF exceeding 99%, highlighting the platform's reliance on SCNAs for accurate TFx detection. Short fragment enrichment (≤150 base pairs) significantly increased TFx values across all samples but could be mapped back to the original TFx values accurately using polynomial curve fitting (R-squared=0.97). Genome- wide fragmentation profiles showed increasing deviation from non-tumor controls as TFx increased, with SCNA-positive samples exhibiting greater deviations than SCNA-negative samples. Conclusions: These findings demonstrate the dependence on sequencing coverage and the presence of SCNAs by current ctDNA analysis methods, highlighting their limitations for accurately detecting ctDNA in challenging scenarios. Citation Format: Nikki Higa, Peter Kuhn, Jesse L Berry, Liya Xu. Assessment of ctDNA analysis methods using high purity ctDNA from the aqueous humor of retinoblastoma eyes [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr B059.

Advantages of Metabolomics-Based Multivariate Machine Learning to Predict Disease Severity: Example of COVID

The COVID-19 outbreak caused saturations of hospitals, highlighting the importance of early patient triage to optimize resource prioritization. Herein, our objective was to test if high definition metabolomics, combined with ML, can improve prognostication and triage performance over standard clinical parameters using COVID infection as an example. Using high resolution mass spectrometry, we obtained metabolomics profiles of patients and combined them with clinical parameters to design machine learning (ML) algorithms predicting severity (herein determined as the need for mechanical ventilation during patient care). A total of 64 PCR-positive COVID patients at the Poitiers CHU were recruited. Clinical and metabolomics investigations were conducted 8 days after the onset of symptoms. We show that standard clinical parameters could predict severity with good performance (AUC of the ROC curve: 0.85), using SpO2, first respiratory rate, Horowitz quotient and age as the most important variables. However, the performance of the prediction was substantially improved by the use of metabolomics (AUC = 0.92). Our small-scale study demonstrates that metabolomics can improve the performance of diagnosis and prognosis algorithms, and thus be a key player in the future discovery of new biological signals. This technique is easily deployable in the clinic, and combined with machine learning, it can help design the mathematical models needed to advance towards personalized medicine.

The Importance of Emotional Intelligence in Direct Leadership in the Army of the Czech Republic

The article deals with application of emotional intelligence for leaders of direct leadership in the Army of the Czech Republic and its connection with the social climate of their units. Emotional intelligence leadership and social climate is a connection that is currently appearing in research activity and doctrinal army documents and explores. The authors try to find and evaluate the benefits and limits of EI in the field of preparation military personnel. From the currently available research, it is precisely the construct of emotional intelligence that appears as one of the possible ways to develop the necessary skills of commanders to facilitate their work with subordinates. Emotional intelligence involves the ability to correctly identify emotions in oneself and in others, to understand emotions and their language, to manage emotions in oneself and in others and use emotions to support cognitive activities and to motivate adaptive behaviour. Direct leadership is the level where leading people is face to face. These are units, where subordinates are used to seeing their commanders every day. For these functions it is still possible and important to create strong relationships, close cooperation and mutual knowledge of all members of the unit. Commanders facing high decision-making demands in an unstable environment. They build working one’s teams with a favourable social climate and support their psychological resilience subordinates. These aspects are decisive for ensuring the tasks of the unit. The main method is quantitative research, which is carried out using a standardized test MSCEIT emotional intelligence in selected commanders of six units and a non-standardized questionnaire "social climate on the units" in their subordinates. Based on obtained results is submitted methodology of development of emotional intelligence for leaders of a platoon. It contains standard parameters. The thesis also formulates recommendation for pedagogical and research activities and output of doctrine leadership.

Search for CP -Violating Neutrino Nonstandard Interactions with the NOvA Experiment

This Letter reports a search for charge-parity (CP) symmetry violating nonstandard interactions (NSI) of neutrinos with matter using the NOvA Experiment, and examines their effects on the determination of the standard oscillation parameters. Data from νμ(ν¯μ)→νμ(ν¯μ) and νμ(ν¯μ)→νe(ν¯e) oscillation channels are used to measure the effect of the NSI parameters ϵeμ and ϵeτ. With 90% CL the magnitudes of the NSI couplings are constrained to be |ϵeμ|≲0.3 and |ϵeτ|≲0.4. A degeneracy at |ϵeτ|≈1.8 is reported, and we observe that the presence of NSI limits sensitivity to the standard CP phase δCP. Published by the American Physical Society 2024

Predictive value of 68[Ga]Ga-DOTA-TATE PET/CT volumetric parameters in assessing treatment response to long-acting somatostatin analogues in patients with well-differentiated neuroendocrine tumours.

Over the past decade, numerous treatment options have emerged for patients with locally advanced and metastatic neuroendocrine tumours (NETs). Nevertheless, the optimal timing of treatment interventions remains uncertain, given the highly variable disease course observed in these patients, even when patients have the same tumour stage and grade. The aim of the study was to evaluate the predictive role of standardized uptake values (SUVs) and volumetric parameters obtained from pretreatment [68Ga]Ga-DOTA-TATE for response to SSA therapy in patients with NET. In this retrospective study, we included 42 patients (21 women, 21 men; age range: 46-84years) with histologically confirmed, metastatic, NET (G1 13, G2 28 cases); median Ki-67 index 5%, range 1-16) who received long acting SSA as a first line treatment and underwent [68Ga]Ga-DOTA-TATE PET/CT before SSA treatment. For all [68Ga]Ga-DOTA-TATE avid lesion SUVmax, SUVmean, somatostatin receptor expression tumour volume (STV), total lesion somatostatin receptor expression (TLD, STV multiplied by SUV mean) and Tmean/Smean (SUVmean of tumours/metastases divided by SUVmean of normal spleen) were measured. Finally, the sum of STV (total STV, TSTV) and TLD (total TLD, TTLD) was calculated for each patient and used in the analysis. During the study period, 14 patients had stable disease (33.3%) and 28 patients experienced progression (66.7%), among whom 12 patients died. The median progression-free survival (PFS) and overall survival (OS) were 26.5 and 46.5months, respectively. In the univariate and multivariate analysis, in the whole population study, Tmean/Smean ratio (HR 1.88, 95% CI 1.06-3.35, p = 0.03), Ki-67 index (HR 1.14, CI 1.03-1.26, p = 0.01) and pre-treatment chromogranin A serum concentration (HR 1.01, CI 1.0-1.03, p = 0.01) were significantly associated with PFS. Among patients with small intestinal NETs, TSTV (< 125.85 cm3 vs. ≥ 125.85 cm3, p = 0.023) and TTLD (< 4168.95 vs. ≥ 4168.95, p = 0.026) were significantly associated with PFS in the univariate analyses. No significant correlation was found between measured volumetric parameters and OS. Volumetric parameters of pretreatment 68[Ga]Ga-DOTA-TATE PET/CT may be useful in prediction of the response to SSA (used in monotherapy as a first-line therapy) in patients with NET.

Prevalence of comorbid autoimmune diseases and antibodies in newly diagnosed multiple sclerosis patients.

Diagnosing multiple sclerosis (MS) is challenging due to diverse symptoms and the absence of specific biomarkers. Concurrent autoimmune diseases (AID) or non-specific antibodies further complicate diagnosis, progression monitoring, and management. Data on AID prevalence in MS patients are sparse. This study aims to identify concurrent AIDs alongside MS. In this retrospective single-center study, we analyzed patient records at our university hospital from 2010 to 2017, focusing on cases suspected of inflammatory demyelinating disease. The 2017 McDonald criteria were applied. Additionally, we measured neurofilament light (NfL) levels from available CSF samples in our biobank. We identified a total of 315 patients, of whom 66% were women. In total, 13.7% of all patients had concurrent AID, while 20.3% had isolated antibody findings without AID. The most common AID was autoimmune thyroiditis (8.9%), followed by chronic inflammatory skin diseases (1.6%), arthritis (1%), type 1 diabetes (1%), Sjögren's syndrome (0.6%), and inflammatory bowel diseases (0.6%). Cardiolipin antibodies were the most frequent isolated antibodyfinding (8.6%). Our data showed that, from the perspective of the initial demyelinating event, neither comorbid AID nor isolated antibodies significantly influenced relapses or MS progression over a median follow-up of 9months. Standard CSF parameters and NfL levels were similar between the groups at the time of MS diagnosis. Our study shows that AIDs, particularly autoimmune thyroiditis, frequently occur at the onset of MS. The proportion of AIDs commonly treated with immunomodulatory therapy in our cohort was similar to that observed in the general population. Comorbid AID did not affect NfL levels, indicating similar disease activity. Future research should explore new AID emergence during the course of MS, especially considering the increased incidence of rheumatic diseases later in life.

Abstract 4137682: Genome wide association study for residualized apolipoprotein B elucidates its role in coronary artery disease risk

Background: Recent studies have shown apolipoprotein B (ApoB), the principle atherogenic lipoproteins, to have greater predictive ability for coronary artery disease (CAD) risk over standard lipid parameters. Moreover, discordantly high ApoB relative to Low-density lipoprotein cholesterol (LDLC) has repeatedly been associated with increased CAD risk. Aim: Given the strong genetic effects of ApoB and LDLC, we sought to characterize the discordance between ApoB and LDLC by genetics to obtain mechanistic insights into this emerging risk factor. Method: We derived residualized-ApoB regressing ApoB on LDLC in European-like populations (N = 383,500) in the UK Biobank. Using residualized-ApoB as an outcome, we explored clinical associations and conducted genome wide association study (GWAS). Result: Residualized-ApoB only modestly correlated with ApoB and LDLC (Spearman’s rho = 0.248 and -0.0079 respectively). We observed increased residualized-ApoB in males and individuals with lipid lowering therapy. Increased residualized-ApoB was associated with increased risk for CAD [Odds Ratio; 1.25 (95% Confidence interval 1.23-1.27)] independent from LDLC, ApoB, and Triglycerides. By GWAS, we observed significant heritability for residualized-ApoB [h 2 = 12.3 (SE 0.012)] and 195 significantly associated genetic loci ( P &lt; 5 × 10 -8 ). Only 59 of these lead variants were associated with ApoB or LDLC. We also found different effects in ApoB-related loci. For example, ApoB-increasing alleles at APOB (rs533617) and APOE (rs7412) loci increased residualized-ApoB but ApoB-increasing alleles at ABCG8 (rs4245791) and HAPLN4-TM6SF2 (rs150641967) loci decreased residualized-ApoB. Conclusions: Exploiting genetics, we determined significant heritability of residualized-ApoB which was partially correlated with ApoB/LDLC. We identified distinct effects of genetic variants on residualized-ApoB. Our results provide the clues for further precise understanding of regulatory mechanisms between ApoB and LDLC.

Improving -inhomogeneity tolerance by resolving non-bijection in MP2RAGE R1 mapping: A 2D look-up table approach demonstrated at 3 T.

Regarding in vivo, robust longitudinal relaxation rate (R1) mapping, the goal of the present paper is two-fold. First, to verify that non-bijective mapping in magnetization-prepared 2 rapid gradient echo (MP2RAGE) imaging can be resolved through a two-dimensional look-up table approach. Second, that the expanded parameter space from this can be used to improve -inhomogeneity tolerance without other prerequisites. By deriving a second contrast from the magnitude images of the MP2RAGE acquisition, ambiguities in the original MP2RAGE image resulting from non-bijective transfer curves can be resolved. Such ambiguities may occur when protocols are optimized, such as for higher -inhomogeneity tolerance. A 2D look-up table approach combines the available information to resolve these ambiguities during mapping. At 3 T, we acquired MP2RAGE images with standard acquisition parameters and (non-bijective) parameters optimized for -inhomogeneity tolerance. From 3 subjects across multiple sessions, we assessed the -inhomogeneity tolerance through excitation-pulse amplitude scalings. The R1 maps resulting from the -optimized protocols showed greatly reduced effects across images but without additional scanner time. Meanwhile, these maps could only successfully be derived by a 2D look-up table approach. We show that it is possible to optimize for -inhomogeneity tolerance in MP2RAGE through sequence-parameter settings, while still successfully estimating the R1 map with a two-dimensional look-up table approach. This without the need for an additional map. The increased parameter space enabled by the two-dimensional look-up table approach may further be used to adjust MP2RAGE acquisitions for improved scan times, signal-to-noise ratio, and/or contrast-to-noise ratio.

Prediction of Fragility Fractures and Mortality in a Cohort of Geriatric Patients.

Risk factors of refracture after fragility fractures include osteoporosis, female gender and advanced age among others. We hypothesized that the assessment of functionality, muscle health and nutrition status contribute to the risk prediction for further fractures and death. We assessed 334 patients admitted to the department of acute geriatrics for sociodemographic data, bone fragility, selected laboratory tests, body composition and data on functionality using the comprehensive geriatric assessment. Patients had follow-ups until the occurrence of further fractures or death. Dual-energy X-ray absorptiometry and pulse echo measurements were performed to assess bone mineral density. Fracture risk was assessed using the FRAX score and muscle strength according to published guidelines on sarcopenia. The mean age was 81 years (70-95), and 82.3% (275/334) were women. An incidence of 10.4% (35/334) new fragility fractures was observed within 24 months, and the mortality rate was 12.2% (41/334). A significantly higher rate of further fractures was associated with lower BMI (body mass index) (HR 0.925, CI 0.872-0.98; p = 0.009), lower parathyroid hormone levels (HR 0.986, CI 0.973-0.998; p = 0.026) and with the diagnosis of osteoporosis (HR 2.546, CI 1.192-5.438; p = 0.016). No significant associations were present in patients with previous fractures, with higher age, higher FRAX scores, sarcopenia, in women, sarcopenic obesity, frail patients, lower grip strength, lower walking speed, lower Barthel index or lower DI (density index) values. The predictive power for further fractures was 10.7% higher adding osteosarcopenia, BMI and parathyroid hormone levels to standard assessment parameters osteoporosis, age and the status of previous fractures. Mortality was significantly higher with advanced age (HR 1.101, CI 1.052-1.151; p < 0.001), in men (HR 6.464, CI 3.141-13.305; p < 0.001), in smokers (p = 0.002), higher FRAX score (HR 1.039, CI 1.009-1.070; p = 0.010), lower renal function (HR 0.987, CI 0.976-0.997; p = 0.010), lower Tinetti test scores (HR 0.943, CI 0.900-0.987; p = 0.012), lower walking speed (HR 0.084, CI 0.018-0.382; p = 0.001), lower hand grip (HR 0.876, CI 0.836-0.919; p < 0.001) and lower Barthel index scores (HR 0.984, CI 0.971-0.997; p = 0.015). In a cohort of geriatric patients, the addition of BMI, low parathyroid hormone levels and osteosarcopenia increases the predictive power for further fractures by 10.7%. These parameters are a valuable addition to the standard assessment parameters age and history of sustained fractures. Mortality is partly associated with potentially treatable functional parameters.

Application of Quantitative Proton Nuclear Magnetic Resonance Spectroscopy for Determination of the Content of Geniposide in Gardeniae fructus

Background: Gardeniae fructus (Zhi-Zi) is the dry ripe fruit of the plant Gardenia jasminoides Ellis (Rubiaceae), which can be used as both food and medicine. Geniposide, a key constituent of Gardeniae fructus, serves as an indicator component for evaluating the quality of Gardeniae fructus. Traditionally, the quantification of geniposide in Gardeniae fructus is achieved through High-performance Liquid Chromatography (HPLC)-based methods. Objective: The present study aimed to introduce a rapid approach to quantifying geniposide content in Gardeniae fructus along with validating its effectiveness. Methods: The experiments involved finding a suitable deuterium solvent, Internal Standard (IS), specific peak, and Nuclear Magnetic Resonance (NMR) parameters for quantitation, and validating specificity, accuracy, precision, and stability. Results: The results have indicated that methanol-d4 as a solvent has facilitated excellent signal separation in the proton Nuclear Magnetic Resonance (1H NMR) spectroscopy, with trimethyl 1,3,5- benzenetricarboxylate emerging as the ideal IS. The specific signal at δ 7.45, corresponding to H-3 in geniposide, has been identified as the optimal peak for integration. The application of distinctive signals from the 1H NMR spectroscopy has allowed for the precise quantification of geniposide in Gardeniae fructus. Conclusion: This study has suggested using 1H NMR to quantify geniposide in Gardeniae fructus to be a viable alternative to HPLC-based methods, providing a suitable approach for quality control of Gardeniae fructus.

Bridging the Gap: linking Torulaspora delbrueckii Genotypes to Fermentation Phenotypes and Wine Aroma.

Climate change and consumer preferences are driving innovation in winemaking, with a growing interest in non-Saccharomyces species. Among these, Torulaspora delbrueckii (Td) has gained recognition for its ability to reduce volatile acidity and enhance aromatic complexity in wine. However, knowledge regarding its phenotypic and genomic diversity impacting alcoholic fermentation remains limited. Aiming to elucidate the metabolic differences between Td and Saccharomyces cerevisiae (Sc) and the Td intraspecies diversity, we conducted a comprehensive metabolic characterization of fifteen Td strains. This analysis delved beyond standard fermentation parameters (kinetics and major metabolites production) to explore non-conventional aromas and establish genotype-phenotype links. Our findings confirmed that most Td strains produce less acetic acid and more succinate and glycerol than Sc. The overall aromatic profiles of Td strains differed from Sc, exhibiting higher levels of monoterpenes and higher alcohols, while producing less acetate esters, fatty acids, their corresponding ethyl esters, and lactones. Moreover, we identified the absence of genes responsible for specific aroma profiles, such as decreased ethyl esters production, as well as the absence of cell wall genes, which might negatively affect Td performance when compared to Sc. This work highlights the significant diversity within Td and underscores potential links between its genotype and phenotype.

Common laboratory results-based artificial intelligence analysis achieves accurate classification of plasma cell dyscrasias.

Plasma cell dyscrasias encompass a diverse set of disorders, where early and precise diagnosis is essential for optimizing patient outcomes. Despite advancements, current diagnostic methodologies remain underutilized in applying artificial intelligence (AI) to routine laboratory data. This study seeks to construct an AI-driven model leveraging standard laboratory parameters to enhance diagnostic accuracy and classification efficiency in plasma cell dyscrasias. Data from 1,188 participants (609 with plasma cell dyscrasias and 579 controls) collected between 2018 and 2023 were analyzed. Initial variable selection employed Kruskal-Wallis and Wilcoxon tests, followed by dimensionality reduction and variable prioritization using the Shapley Additive Explanations (SHAP) approach. Nine pivotal variables were identified, including hemoglobin (HGB), serum creatinine, and β2-microglobulin. Utilizing these, four machine learning models (gradient boosting decision tree (GBDT), support vector machine (SVM), deep neural network (DNN), and decision tree (DT) were developed and evaluated, with performance metrics such as accuracy, recall, and area under the curve (AUC) assessed through 5-fold cross-validation. A subtype classification model was also developed, analyzing data from 380 cases to classify disorders such as multiple myeloma (MM) and monoclonal gammopathy of undetermined significance (MGUS). 1. Variable selection: The SHAP method pinpointed nine critical variables, including hemoglobin (HGB), serum creatinine, erythrocyte sedimentation rate (ESR), and β2-microglobulin. 2. Diagnostic model performance: The GBDT model exhibited superior diagnostic performance for plasma cell dyscrasias, achieving 93.5% accuracy, 98.1% recall, and an AUC of 0.987. External validation reinforced its robustness, with 100% accuracy and an F1 score of 98.5%. 3. Subtype Classification: The DNN model excelled in classifying multiple myeloma, MGUS, and light-chain myeloma, demonstrating sensitivity and specificity above 90% across all subtypes. AI models based on routine laboratory results significantly enhance the precision of diagnosing and classifying plasma cell dyscrasias, presenting a promising avenue for early detection and individualized treatment strategies.

Effect of Nd:YAG Laser Irradiation of the Growth of Oral Biofilm

Background: Oral microbiota comprises a wide variety of microorganisms. The purpose of this study was to evaluate the effects of Nd:YAG laser with a 1064 nm wavelength on the in vitro growth of Candida albicans, Candida glabrata, and Streptococcus mutans clinical strains, as well as their biofilm. The study also aimed to determine whether the parameters recommended for photobiomodulation (PBM) therapy, typically used for tissue wound healing, have any additional antibacterial or antifungal effects. Material and Methods: Single- and dual-species planktonic cell solution and biofilm cultures of Streptococcus mutans, Candida albicans, and Candida glabrata were irradiated using an Nd:YAG laser (LightWalker; Fotona; Slovenia) with a flat-top Genova handpiece. Two test groups were evaluated: Group 1 (G-T1) exposed to low power associated parameters (irradiance 0.5 W/cm2) and Group 2 (G-T2) with higher laser parameters (irradiance 1.75 W/cm2). Group 3 (control) was not exposed to any irradiation. The lasers’ effect was assessed both immediately after irradiation (DLI; Direct Laser Irradiation) and 24 h post-irradiation (24hLI) of the planktonic suspension using a quantitative method (colony-forming units per 1 mL of suspension; CFU/mL), and the results were compared with the control group, in which no laser was applied. The impact of laser irradiation on biofilm biomass was assessed immediately after laser irradiation using the crystal violet method. Results: Nd:YAG laser irradiation with photobiomodulation setting demonstrated an antimicrobial effect with the greatest immediate reduction observed in S. mutans, achieving up to 85.4% reduction at the T2 settings. However, the laser’s effectiveness diminished after 24 h. In single biofilm cultures, the highest reductions were noted for C. albicans and S. mutans at the T2 settings, with C. albicans achieving a 92.6 ± 3.3% reduction and S. mutans reaching a 94.3 ± 5.0% reduction. Overall, the T2 settings resulted in greater microbial reductions compared to T1, particularly in biofilm cultures, although the effectiveness varied depending on the microorganism and culture type. Laser irradiation, assessed immediately after using the crystal violet method, showed the strongest biofilm reduction for Streptococcus mutans in the T2 settings for both single-species and dual-species biofilms, with higher reductions observed in all the microbial samples at the T2 laser parameters (p &lt; 0.05) Conclusion: The Nd:YAG laser using standard parameters typically applied for wound healing and analgesic effects significantly reduced the number of Candida albicans; Candida glabrata; and Streptococcus mutans strains.

A Design and Safety Analysis of the “Electricity-Hydrogen-Ammonia” Energy Storage System: A Case Study of Haiyang Nuclear Power Plant

With the development of modernization, traditional fossil energy reserves are decreasing, and the power industry, as one of the main energy consumption forces, has begun to pay attention to increasing the proportion of clean energy generation. With the deepening of electrification, the peak-valley difference of residential electricity consumption increases, but photovoltaic and wind power generation have fluctuations and are manifested as reverse peak regulation. Thermal power plants as the main force of peak regulation gradually reduce the market share, making nuclear power plants bear the heavy responsibility of participating in peak regulation. The traditional method of adjusting operating power by inserting and removing control rods has great safety risks and wastes resources. Therefore, this paper proposes a new energy storage system that can keep the nuclear power plant running at full power and produce hydrogen to synthesize ammonia from excess power. A comprehensive evaluation model of energy storage based on z-score data standardization and objective parameter assignment AHP (analytic hierarchy process) analysis method was established to evaluate energy storage systems according to a multi-index system. With an AP1000 daily load tracking curve as the input model, the simulation model built by Aspen Plus V14 was used to calculate the operating conditions of the system. In order to provide a construction basis for practical engineering use, Haiyang Nuclear Power Plant in Shandong Province is taken as an example. The system layout scheme is proposed according to the local environmental conditions. The accident tree analysis method is combined with ALOHA 5.4.1.2 (Areal Locations of Hazardous Atmospheres) hazardous chemical analysis software and MARPLOT 5.1.1 geographic information technology. A qualitative and quantitative assessment of risk factors and the consequences of leakage, fire, and explosion accidents caused by hydrogen and ammonia storage processes is carried out to provide guidance for accident prevention and emergency rescue. The design of an “Electric-Hydrogen-Ammonia” energy storage system proposed in this paper provides a new idea for zero-carbon energy storage for the peak shaving of nuclear power plants and has a certain role in promoting the development of clean energy.

Evaluating process parameters of SLS part of polyamide-12 recycled powder using RSM

Abstract Selective laser sintering (SLS) is a highly flexible rapid prototyping (RP) technology which can use a wide range of powdered materials to generate high quality complex geometries directly from digital models. The SLS process uses a laser to sinter selected areas of powdered materials to produce solid objects layer by layer, according to the 2D data obtained from CT scan or MRI imaging techniques. This paper presents research work for evaluating the effect of process parameters on impact toughness and surface roughness of the part manufactured on Farsoon SS402P SLS from recycled ageing FS 3300PA which is PA-12 based powder and standard operating parameters using Response Surface Methodology (RSM) design of experiments. Impact tests have been performed as per the ASTM D6110 standard using recommendations from ISO 179-2. According to the results, effect of process parameters are successfully analyzed by employing impact toughness and surface roughness tests. Based on the results of the ANOVA analysis, impact toughness increases with increasing laser power (4.467 j/cm2 at 72.5 watts). Similarly, it is also clear from the results that the region with the lowest laser power, high layer thickness, and 90-degree orientation had the lowest surface roughness (3.46 μm).

Recycled graphite enabled superior performance for lithium ion batteries

Recycling graphite attracts growing attention since cumulative amount of spent Li-ion batteries and the shortage of graphite supply chain. Although various recycling methods have been reported, the recycled graphite cannot reach the strict commercial standards of purity, scalability, efficiency, and capacity, preventing it from battery manufacturing. Herein, the important roles of defects and functional groups on the graphite surface are deeply studied, and a closed-loop graphite recycling process with the surface recovery and modification for the graphite from the end-of-life batteries is demonstrated. The recovered graphite delivers a purity of over 99.9 % and an average initial coulombic efficiency of 91.5 %. Compared with commercial graphite in industrial standard battery testing parameters, full cells with recovered graphite possess enhanced rate reversibility, doubled cycle life, over 10 % higher capacity along with half anode material cost. These impressive results not only underscore the transformative potential of surface reconstruction and modification in graphite recycling, but also present economic feasibility and sustainable pathway for significantly improving battery performance and addressing global resource challenges via integration with the hydrometallurgical recycling process.

Mutations of ARID1B, PIK3C2B, KMT2B, and FAT1 genes influence clinical outcome in newly diagnosed myeloma

The study aimed to elucidate the mutational profile of patients with newly diagnosed multiple myeloma to understand correlations of alterations with clinical outcomes. A cohort of 20 patients was enrolled, and mutational analysis was conducted using the TruSight Oncology 500 DNA Kit. Identified genetic alterations were related to clinicopathologic features and treatment outcomes. A total of 724 high-quality variants were validated. All patients harbored mutations associated with the RTK-RAS pathway, with over half having alterations in PI3K, NOTCH, and WNT pathways. Several gene mutations were associated with specific clinical characteristics and prognostic indicators, revealing a complex interplay between genetic alterations and myeloma type, standard prognostic indicators, biochemical parameters, and renal function. Genetic alterations significantly influencing progression-free survival concerned PIK3C2B, ARID1B genes, and concomitant mutations in KMT2B, FAT1, and ARID1B. The findings underscore the potential of gene mutation-based prognostic tools in enhancing clinical decision-making and suggest that further exploration of identified genetic markers could pave the way for improved prognostic stratification and targeted therapeutic interventions in multiple myeloma.

Chest wall deformities in CDH survivors Children with CDH are at high risk for pectus excavatum deformity and progressive thoracic asymmetry

BackgroundCongenital diaphragmatic hernia (CDH) survivors exhibit an increased risk for developing musculoskeletal anomalies. This prospective long-term cohort study investigates the characteristics, predictors and dynamic changes of different chest wall deformities in a large cohort of CDH patients. MethodsAll children diagnosed with CDH and treated at the University Hospital Mannheim from 2010 to 2023 were included. Thoracic morphology was evaluated based on 740 CT or MRI scans and statistical analysis was performed using the Mann-Whitney-U-Test, Fisher’s Exact Test and Spearman’s correlation. P-values<0.05 were considered statistically significant. ResultsOut of 1,216 children with CDH, 548 received cross-sectional imaging examinations of the chest within the follow-up program. Mean Haller Index was 2.62 ± 0.55 and pectus excavatum deformity was present in 34.09% of CDH patients. Thoracic asymmetry in favor of the right hemithorax was present in 45.90% and showed a pronounced age-related progression. The severity of chest wall deformities showed a significant correlation with prenatal diagnosis, liver herniation, lower lung to head ratio and fetal relative lung volume, use of ECMO and inhaled nitric oxide, diaphragmatic patch closure and laparotomy. ConclusionChildren with CDH show an increased incidence of chest wall deformities, including pectus deformity and asymmetry with the potential for significant age-related progression. Measurement of thoracic morphology using standardized parameters based on MRI or CT scans should be implemented as an essential component of standardized follow-up programs. Rigorous randomized, controlled intervention trials are required to evaluate whether certain therapies can alter the trajectory of these chest wall deformities.