Changes in health-related quality of life in common variable immunodeficiency: an eight-year journey, including the COVID-19 pandemic.

BACKGROUND: Personalized medicine requires the assessment of the impact of health care interventions on Health-Related Quality of Life. RESEARCH DESIGN AND METHODS: We run an observational study of HRQoL in 140 CVID patients with biannual assessments over 8 years using a disease-specific tool, the CVID_QoL, and the GHQ questionnaires. Factors influencing changes in HRQoL scores were identified using multiple linear regression models with a stepwise procedure. RESULTS: Infections frequency, female gender, and chronic enteropathy were associated with worse global CVID_QoL scores. The presence of permanent organ damage and older age contributed to the perception of being at risk of health deterioration, while chronic enteropathy was associated with fatigue. The presence of permanent organ damage was also associated with perceived difficulties in usual activities. The frequency of infections was the main risk factor for difficulties in long-term planning and perceptions of vulnerability. Before COVID-19, improved HRQoL scores were associated with reduced respiratory infections and changes in immunoglobulin replacement route and setting. The COVID-19 pandemic caused a sudden deterioration in all HRQoL dimensions, and a further deterioration in the emotional dimension was observed during the pandemic period. Patients who died during the study had worse CVID_QoL scores at all time points, confirming that HRQoL performance is strongly related to patient outcome. CONCLUSIONS: Periodic HRQoL assessments are needed to capture relevant issues that change over time in patients affected by long-term chronic conditions such CVID, possibly identifying areas of intervention.

High body mass index is associated with elevated risk of perioperative ischemic stroke in patients who underwent noncardiac surgery: A retrospective cohort study.

BACKGROUND: Body mass index (BMI) serves as a global metric for assessing obesity and overall health status. However, the impact of BMI, treated as a continuous variable, on the risk of perioperative stroke remains poorly understood. This retrospective cohort study aimed to elucidate the association between BMI and the risk of perioperative ischemic stroke in patients undergoing non-cardiovascular surgery. METHODS: A cohort of 223,415 patients undergoing noncardiac surgery at the First Medical Center of Chinese PLA General Hospital between January 1, 2008 and August 31, 2019 was screened. Preoperative high BMI, defined as BMI >22.64 kg/m2, was the primary exposure, and the outcome of interest was the new diagnosis of perioperative ischemic stroke within 30 days post-surgery. Robust controls for patient and intraoperative factors were implemented to minimize residual confounding. Logistic regression and propensity score matching were employed, and patients were stratified into subgroups for further investigation. RESULTS: The overall incidence of perioperative ischemic stroke was 0.23% (n = 525) in the cohort. After adjusting for patient-related variables (OR 1.283; 95% CI, 1.04-1.594; p < 0.05), surgery-related variables (OR 1.484; 95% CI, 1.2-1.849; p < 0.001), and all confounding variables (OR 1.279; 95% CI, 1.025-1.607; p < 0.05), patients with BMI >22.64 kg/m2 exhibited a significantly increased risk of perioperative ischemic stroke. This association persisted in the propensity score matched cohort (OR 1.577; 95% CI, 1.203-2.073; p < 0.01). Subgroup analyses indicated that preoperative BMI >22.64 kg/m2 correlated with an elevated risk of perioperative ischemic stroke in female patients, those with coronary heart disease, peripheral vascular diseases, and individuals undergoing neurosurgery. CONCLUSION: We first identified BMI >22.64 kg/m2 as a substantial and independent risk factor for perioperative ischemic stroke in Chinese noncardiac surgery patients. Normal BMI may not suffice as a universal preventive standard. Instead, a more stringent perioperative weight management approach is recommended, particularly for specific subgroups such as female patients, those with coronary heart disease and peripheral vascular disease, and individuals scheduled for neurosurgery.

Factors associated with intention of HIV testing among Asian American men: a path analysis.

Research has pointed to myriad cultural and socio-psychological factors associated with HIV testing, such as acculturation, social norms about HIV testing, masculinity, homonegativity, and constructs from the Theory of Planned Behavior. However, the interrelationships of these factors on the intentions of HIV testing among the population of Asian American men remains unknown. A dataset of 425 Asian American men in the U.S., collected online with convenience sampling method during 2020-2021, was analyzed to test a conceptual framework that aimed to fill this gap. Results from a path model with two endogenous variables (homonegativity and HIV testing intention) indicated that perceived social norms about HIV testing, attitude about HIV testing, and perceived HIV risk had directandindirect relationships with the intentions of HIV testing in the study population. However, social norms about HIV testing and perceived HIV risk showed stronger direct effects (standardized estimates = 0.37 and 0.34, respectively, p-value < 0.001). Additionally, we found that the relationships of these factors with HIV testing intention were also mediated by homonegativity. Findings from this study advance our understanding of pathways of associations between a host of cultural and socio-psychological factors with HIV testing intention among an understudied population - Asian American men. Our results will help inform the development of future intervention programs to increase HIV testing in this population.

Cancer Antibody Engineering: Comparison of Mammalian, Yeast, Bacterial, Plants, Cell-free and Hybridoma Expression Systems.

BACKGROUND: Cancer is a significant issue worldwide. Generally, commercially available treatments, such as surgery, radiotherapy, and chemotherapy, are associated with undesirable complications. Hence, immunotherapy serves as a crucial alternative to those treatment options. OBJECTIVE: This modality is aimed to boost the immune system through the application of engineered antibodies, which can be produced using recombinant DNA technology. RESULTS: The discussion of the technologies leads to an introduction of the single-chain variable fragment (scFv). Thereafter, the advantages, disadvantages, and challenges associated with different expression systems, such as mammalian cells, yeast cells, bacterial cells, plant cells, and phage display were discussed comprehensively. CONCLUSION: Furthermore, conventional approaches such as hybridoma and modern approaches such as cell-free protein synthesis (CFPS) and simple colony assays are included. In short, this article has compiled evidence relating to each display system and may serve as a reference for those who aim to explore antibody engineering using one of the methods listed in this article.

Case Report: Common variable immunodeficiency phenotype and granulomatous-lymphocytic interstitial lung disease with a novel SOCS1 variant.

Common variable immunodeficiency is a heterogeneous symptomatic group of inborn errors of immunity that mainly affects antibodies production and/or function, predisposing patients to recurrent and severe infections. More than half of them usually develop autoimmunity, lymphoproliferation, enteropathy, and malignancies. Among these conditions, chronic lung disease such as granulomatous-lymphocytic interstitial lung disease is one of the leading causes of death in these patients. Recently, many genes that play a key role in B and T cells' development, maintenance, and/or cytokines signaling pathways have been implicated in the pathogenesis of the disease. Here, we describe the first Argentinian patient presenting with common variable immunodeficiency and granulomatous-lymphocytic interstitial lung disease, harboring two in cis heterozygous variants in the SOCS1 gene.

The clinical and immunological characteristics of common variable immunodeficiency in adults and older adults.

OBJECTIVE: The aim of this study was to determine the clinical and immunological characteristics of older adults with common variable immunodeficiency (CVID). METHODS: Patients aged ≥18 years who were followed up with the diagnosis of CVID between 2015 and 2020 were included in the study. The patients were separated into two age groups according to the age at diagnosis: the adult group, aged 18-65 years (n=49) and the older adult group, aged ≥65 years (n=11). RESULTS: Splenomegaly (55.1% vs. 9.1%, p=0.006), bronchiectasis (53.0% vs. 9.1%, p=0.008), and autoimmunity (42.8% vs. 9.1%, p=0.036) were determined to be more common in the adult group than in the older adults. A similar frequency of malignancy was seen in both groups (6.1% vs. 9.1%, p=0.721). There were significantly more patients with no comorbidity in the older adult group than in the adult group (45.5% vs. 16.3%, p=0.034). Serum IgG and IgA levels were determined to be significantly higher in the older adult group than in the adult group (p=0.001 for all). The CD19+ B-cell count at the time of diagnosis was determined to be lower and the CD19+CD27+IgD- switched memory B-cells and CD16+CD56+ natural killer cell counts were higher in the older adults than in the adult group (p=0.016, p=0.032, p=0.044, respectively). CONCLUSION: Knowledge of clinical and immunological differences in older adult CVID patients may be of benefit in polyclinic follow-up and in respect of changes to be made to the treatment plan.

Cross polarization stability in multidimensional NMR spectroscopy of biological solids.

Magic-angle spinning (MAS) solid-state nuclear magnetic resonance (SSNMR) spectroscopy is a powerful and versatile technique for probing structure and dynamics in large, insoluble biological systems at atomic resolution. With many recent advances in instrumentation and polarization methods, technology development in SSNMR remains an active area of research and presents opportunities to further improve data collection, processing, and analysis of samples with low sensitivity and complex tertiary and quaternary structures. SSNMR spectra are often collected as multidimensional data, requiring stable experimental conditions to minimize signal fluctuations (t1 noise). In this work, we examine the factors adversely affecting signal stability as well as strategies used to mitigate them, considering laboratory environmental requirements, configuration of amplifiers, and pulse sequence parameter selection. We show that Thermopad® temperature variable attenuators (TVAs) can partially compensate for the changes in amplifier output power as a function of temperature and thereby ameliorate one significant source of instability for some spectrometers and pulse sequences. We also consider the selection of tangent ramped cross polarization (CP) waveform shapes, to balance the requirements of sensitivity and instrumental stability. These findings collectively enable improved stability and overall performance for CP-based multidimensional spectra of microcrystalline, membrane, and fibrous proteins performed at multiple magnetic field strengths.

Retention forestry as a climate solution: Assessing biomass, soil carbon and albedo impacts in a northern temperate coniferous forest.

Forest management pathways for nature-based climate solutions, such as variable retention harvesting (VRH), have been gaining traction in recent years; however, their net biochemical and biophysical impacts remain unknown. Here, we use a combination of close-range and satellite remote sensing, eddy covariance technique, and ground-based biometric measurements to investigate forest thinning density and aggregation that maintain ecosystem nutrients, enhance tree growth and provide a negative feedback to the local climate in a northern temperate coniferous forest stand in Ontario, Canada. Our results showed that soil carbon (C) and nitrogen (N) in VRH plots were significantly lower (p < 0.05) for all VRH treatments compared to unharvested plots. On average, soil C was reduced by -0.64 ±â€¯0.22 Δ% C and N by -0.023 ±â€¯0.008 Δ% N in VRH plots. We also observed the largest loss of soil C and N in open areas of aggregate plots. Furthermore, the changes in albedo resulting from VRH treatment were equivalent to removing a large amount of C from the atmosphere, ranging from 1.3 ±â€¯0.2 kg C yr-1 m-2 in aggregate 33 % crown retention plots to 3.4 ±â€¯0.5 kg C yr-1 m-2 in dispersed 33 % crown retention plots. Our findings indicate that spatially dispersed VRH resulted in minimal loss of soil C and N and the highest understory growth and C uptake, while enhanced tree growth and local cooling through increased albedo were observed in dispersed VRH plots with the fewest residual trees. These findings suggest that using the harvested trees from VRH in a way that avoids releasing C into the atmosphere makes dispersed VRH the preferred forest management pathway for nature-based climate solutions.

Variable Duration Trial as an Alternative Design for Continuous Endpoints.

Clinical trials with continuous primary endpoints typically measure outcomes at baseline, at a fixed timepoint (denoted Tmin), and at intermediate timepoints. The analysis is commonly performed using the mixed model repeated measures method. It is sometimes expected that the effect size will be larger with follow-up longer than Tmin. But extending the follow-up for all patients delays trial completion. We propose an alternative trial design and analysis method that potentially increases statistical power without extending the trial duration or increasing the sample size. We propose following the last enrolled patient until Tmin, with earlier enrollees having variable follow-up durations up to a maximum of Tmax. The sample size at Tmax will be smaller than at Tmin, and due to staggered enrollment, data missing at Tmax will be missing completely at random. For analysis, we propose an alpha-adjusted procedure based on the smaller of the p values at Tmin and Tmax, termed minP $$ minP $$ . This approach can provide the highest power when the powers at Tmin and Tmax are similar. If the power at Tmin and Tmax differ significantly, the power of minP $$ minP $$ is modestly reduced compared with the larger of the two powers. Rare disease trials, due to the limited size of the patient population, may benefit the most with this design.

Prediction of steelmaking process variables using K-medoids and a time-aware LSTM network.

A new method is required to address the challenge of predicting process parameters in high-temperature, high-pressure industrial processes. This study proposes a multi-model Long Short-Term Memory (LSTM) network prediction algorithm with irregular time interval sequences to predict the silicon yield in converter steelmaking. The experimental results demonstrate that this algorithm performs better than comparable neural network models in classifying high-dimensional, redundant industrial production data with noise and outliers. The algorithm is evaluated using data from a steel plant. The proposed algorithm has lower errors for predicting the alloy yield than other neural network models. An average mean absolute error (MAE) of less than 0.01 confirms the algorithm's feasibility and practicality.

Applying different levels of practice variability for motor learning: More is not better.

Background: Variable practice is a broadly used tool to improve motor learning processes. However, controversial results can be found in literature about the success of this type of practice compared to constant practice. This study explored one potential reason for this controversy: the manipulation of variable practice load applied during practice and its effects according to the initial performance level and the initial intrinsic variability of the learner. Method: Sixty-five participants were grouped into four practice schedules to learn a serial throwing task, in which the training load of variable practice was manipulated: one constant practice group and three groups with different variable practice loads applied. After a pre-test, participants trained for 2 weeks. A post-test and three retests (96 h, 2 weeks and 1 month) were carried out after training. The participants' throwing accuracy was assessed through error parameters and their initial intrinsic motor variability was assessed by the autocorrelation coefficient of the error. Results: The four groups improved their throwing performance. Pairwise comparisons and effect sizes showed larger error reduction in the low variability group. Different loads of variable practice seem to induce different performance improvements in a throwing task. The modulation of the variable practice load seems to be a step forward to clarify the controversy about its benefits, but it has to be guided by the individuals' features, mainly by the initial intrinsic variability of the learner.

Use of Mendelian randomization to assess the causal status of modifiable exposures for rheumatic diseases.

The explosion in Mendelian randomization (MR) publications is hard to ignore and shows no signs of slowing. Clinician readers, who may not be familiar with jargon-ridden methods, are expected to discern the good from the many low-quality studies that make overconfident claims of causality or stretch the plausibility of what MR can investigate. We aim to equip readers with foundational concepts, contextualized using examples in rheumatology, to appraise the many MR papers that are or will appear in their journals. We highlight the importance of assessing whether exposures are under plausibly specific genetic influence, whether the hypothesized causal pathways make biological sense, and whether results stand up to replication and use of control outcomes. Quality of research can vary substantially using MR as with any design, and all methods have inherent limitations. MR studies have provided and can still contribute valuable insights in the context of evidence triangulation.

Common variable immunodeficiency associated enteropathy: A diagnostic enigma in developing countries.

Common variable immunodeficiency (CVID) is the most prevalent primary immunodeficiency disorder with different phenotypes and aetiologies. It is characterised by hypogammaglobulinaemia, defects in specific antibody response, erroneous activation and proliferation of T cells, leading to increased risk of recurrent infections. In CVID, "Variable" refers to the heterogeneity of clinical presentations, which include recurrent infections, autoimmunity, enteropathy, and increased risk of malignancies. This wide spectrum of disease manifestations and being a diagnosis of exclusion poses a diagnostic challenge. It is pertinent to mention that CVID along with associated complications is the commonest symptomatic primary antibody deficiency but is scarcely mentioned in local literature. The main aim of presenting this case is to impress upon the importance of systematic immunological workup in cases of suspected immunodeficiency to prevent morbidity and mortality.

Inhibition of prefrontal cortex parvalbumin interneurons mitigates behavioral and physiological sequelae of chronic stress in male mice.

Chronic stress leads to hypofunction of the medial prefrontal cortex (mPFC), mechanisms of which remain to be determined. Enhanced activation of GABAergic of parvalbumin (PV) expressing interneurons (INs) is thought to play a role in stress-induced prefrontal inhibition. In this study, we tested whether chemogenetic inhibition of mPFC PV INs after chronic stress can rescue chronic stress-related behavioral and physiological phenotypes. Mice underwent 2 weeks of chronic variable stress (CVS) followed by a battery of behavioral tests known to be affected by chronic stress exposure, e.g. an open field (OF), novel object recognition (NOR), tail suspension test (TST), sucrose preference test (SPT), and light dark (LD) box. Inhibitory DREADDs were actuated by 3 mg/kg CNO administered 30 min prior to each behavioral test. CVS caused hyperactivity in the OF, reduced sucrose preference in the SPT (indicative of enhanced anhedonia), and increased anxiety-like behavior in the LD box. Inhibition of PV IN after stress mitigated these effects. In addition, CVS also resulted in reduced thymus weight and body weight loss, which were also mitigated by PV IN inhibition. Our results indicate that chronic stress leads to plastic changes in PV INs that may be mitigated by chemogenetic inhibition. Our findings implicate cortical GABAergic INs as a therapeutic target in stress-related diseases.

Corrigendum: Patterns of within-host spread of Chlamydia trachomatis between vagina, endocervix and rectum revealed by comparative genomic analysis.

[This corrects the article DOI: 10.3389/fmicb.2023.1154664.].

Linked shrinkage to improve estimation of interaction effects in regression models.

Objectives: The addition of two-way interactions is a classic problem in statistics, and comes with the challenge of quadratically increasing dimension. We aim to a) devise an estimation method that can handle this challenge and b) to aid interpretation of the resulting model by developing computational tools for quantifying variable importance. Methods: Existing strategies typically overcome the dimensionality problem by only allowing interactions between relevant main effects. Building on this philosophy, and aiming for settings with moderate n to p ratio, we develop a local shrinkage model that links the shrinkage of interaction effects to the shrinkage of their corresponding main effects. In addition, we derive a new analytical formula for the Shapley value, which allows rapid assessment of individual-specific variable importance scores and their uncertainties. Results: We empirically demonstrate that our approach provides accurate estimates of the model parameters and very competitive predictive accuracy. In our Bayesian framework, estimation inherently comes with inference, which facilitates variable selection. Comparisons with key competitors are provided. Large-scale cohort data are used to provide realistic illustrations and evaluations. The implementation of our method in RStan is relatively straightforward and flexible, allowing for adaptation to specific needs. Conclusions: Our method is an attractive alternative for existing strategies to handle interactions in epidemiological and/or clinical studies, as its linked local shrinkage can improve parameter accuracy, prediction and variable selection. Moreover, it provides appropriate inference and interpretation, and may compete well with less interpretable machine learners in terms of prediction.

Application of Newton's polynomial interpolation scheme for variable order fractional derivative with power-law kernel.

This paper, offers a new method for simulating variable-order fractional differential operators with numerous types of fractional derivatives, such as the Caputo derivative, the Caputo-Fabrizio derivative, the Atangana-Baleanu fractal and fractional derivative, and the Atangana-Baleanu Caputo derivative via power-law kernels. Modeling chaotical systems and nonlinear fractional differential equations can be accomplished with the utilization of variable-order differential operators. The computational structures are based on the fractional calculus and Newton's polynomial interpolation. These methods are applied to different variable-order fractional derivatives for Wang-Sun, Rucklidge, and Rikitake systems. We illustrate this novel approach's significance and effectiveness through numerical examples.

Enzyme Cascade Amplification-Based Immunoassay Using Alkaline Phosphatase-Linked Single-Chain Variable Fragment Fusion Tracer and MnO2 Nanosheets for Detection of Deoxynivalenol in Corn Samples.

Deoxynivalenol (DON) is a common mycotoxin that contaminates cereals. Therefore, the development of sensitive and efficient detection methods for DON is essential to guarantee food safety and human health. In this study, an enzyme cascade amplification-based immunoassay (ECAIA) using a dual-functional alkaline phosphatase-linked single-chain fragment variable fusion tracer (scFv-ALP) and MnO2 nanosheets was established for DON detection. The scFv-ALP effectively catalyzes the hydrolysis of ascorbyl-2-phosphate (AAP) to produce ascorbic acid (AA). This AA subsequently interacts with MnO2 nanosheets to initiate a redox reaction that results in the loss of oxidizing properties of MnO2. In the absence of ALP, MnO2 nanosheets can oxidize 3,3',5,5'-tetramethylbenzidine (TMB) to produce the blue oxidized product of TMB, which exhibits a signal at a wavelength of 650 nm for quantitative analysis. After optimization, the ECAIA had a limit of detection of 0.45 ng/mL and a linear range of 1.2-35.41 ng/mL. The ECAIA exhibited good accuracy in recovery experiments and high selectivity for DON. Moreover, the detection results of the actual corn samples correlated well with those from high-performance liquid chromatography. Overall, the proposed ECAIA based on the scFv-ALP and MnO2 nanosheets was demonstrated as a reliable tool for the detection of DON in corn samples.

Efficient Aperture Fill Time Correction for Wideband Sparse Array Using Improved Variable Fractional Delay Filters.

To solve the problem of aperture fill time (AFT) for wideband sparse arrays, variable fractional delay (VFD) FIR filters are applied to eliminate linear coupling between spatial and time domains. However, the large dimensions of the filter coefficient matrix result in high system complexity. To alleviate the computational burden of solving VFD filter coefficients, a novel multi-regultion minimax (MRMM) model utilizing the sparse representation technique has been presented. The error function is constrained by the introduction of L2-norm and L1-norm regularizations within the minimax criterion. The L2-norm effectively resolves the problems of overfitting and non-unique solutions that arise in the sparse optimization of traditional minimax (MM) models. Meanwhile, the use of multiple L1-norms enables the optimal design of the smallest sub-filter number and order of the VFD filter. To solve the established nonconvex model, an improved sequential-alternating direction method of multipliers (S-ADMM) algorithm for filter coefficients is proposed, which utilizes sequential alternation to iteratively update multiple soft-thresholding problems. The experimental results show that the optimized VFD filter reduces system complexity significantly and corrects AFT effectively in a wideband sparse array.

Modeling habitat suitability of Dorema ammoniacum D Don. in the rangelands of central Iran.

The purpose of this study was to evaluate the predictive accuracy of habitat suitability models, identifying the potential distribution range of Dorema ammoniacum, and its habitat requirements in the rangelands of Yazd province, central Iran. Bafgh, Mehriz and Nadoushan, were three habitats that were identified, and sampling was conducted in each habitat using a random-systematic method. A set of 10 plots were established (at equal distances) along 350 m long 18 transects. Soil samples (two depths: 0-30 and 30-60 cm from 36 profiles) were collected and measured in the laboratory. Elevation, slope, and aspect maps were derived, and climate information was collected from nearby meteorological stations. The habitat prediction of the species was modeled using Logistic Regression (LR), Maximum Entropy (MaxEnt), and Artificial Neural Network (ANN). The Kappa coefficient and the area under the curve (AUC) were calculated to assess the accuracy of the forecasted maps. The LR model for habitat prediction of the studied species in Mehriz (K = 0.67) and Nadoushan (K = 0.56) habitats were identified as good. The MaxEnt model predicted the habitat distribution for the selected species in Bafgh and Mehriz habitats as excellent (K = 0.89, AUC = 0.76, K = 0.89, AUC = 0.98), and in the Nadoushan habitat as very good (K = 0.78, AUC = 0.85). However, the ANN model predicted Bafgh and Nadoushan habitats as excellent and Mehriz habitat as very good (K = 0.87, K = 0.90, and K = 0.63, respectively). In general, in order to protect species D. ammoniacum, the development of its habitats in other areas of Yazd province and the habitats under study in conservation programs should be given priority.