Small Sample Research Articles

Epidemiology of obesity during pregnancy in Europe: a systematic review

Abstract Background Obesity during pregnancy poses inter-generational health risks and places added burden on healthcare systems. Characterising levels of obesity during pregnancy is necessary to guide future research, policy and practice. Methods The systematic review was performed according to PRISMA guidelines. PubMed, Embase and Web of Science were searched. Studies published between 2009 and 2023 that report the prevalence of obesity during pregnancy in countries in the World Health Organization (WHO) European region were eligible. The Joanna Briggs Institute Prevalence Critical Appraisal tool was used. Two reviewers screened studies independently. A single reviewer completed data extraction and quality assessments, a second checked 20% of extractions and a third resolved disagreements. Narrative synthesis was completed. Results 100 studies reporting the prevalence of obesity during pregnancy in the WHO European region were identified. 59% from Western Europe, 36% Northern, 4% Southern and 1% Eastern. Data within the studies was collected between 1950 and 2019. 35% of studies reported national estimates, 65% regional. 39% studies had measured height and weight, 34% did not report how either were ascertained, 6% used self-report for both, 17% had self-reported height but measured weight, 4% a mixture of self-report and measurement. The smallest sample was 157 while the largest was 1,891,097. Estimated prevalence of obesity during pregnancy ranged from 2.3% (Sweden, data collected 1982-1989) to 28.3% (England, 2007). Conclusions This review identifies variation in the prevalence of obesity during pregnancy in the WHO European region. This may reflect diverse sociocultural contexts, different methodological approaches and temporal trends. There was limited evidence available for Southern and Eastern Europe. Key messages • There are high levels of obesity during pregnancy within the WHO European region. • Enhanced primary prevention and resourcing of obstetric services is needed.

Association between Jewish religious observance and mental health among Israeli adults: Findings from the Global Flourishing Study.

This study investigates the association between Jewish religious observance and several indicators of mental health and psychological well-being among Jewish Israeli adults. Data are from adult (18+) Jewish respondents in the Israeli sample (N = 2958) of the first wave of the Global Flourishing Study (GFS), a 22-nation population survey which will eventually consist of five annual waves of panel data. The GFS Israeli data were collected via a randomized, stratified, probability-based sampling design, and contained dozens of indicators of sociodemographic, socioeconomic, political, religious, health-related, and other constructs. Measures of Jewish religious observance, including religious service attendance, prayer, scripture reading, belief in God, and importance of Judaism, are statistically significant predictors of several single-item indicators of mental health (overall mental health, depression, anxiety) and psychological well-being (suffering, happiness, life satisfaction). Greater religious observance is associated with a higher self-rating of overall mental health, less depression and anxiety, less suffering, and greater happiness and life satisfaction. Nearly all results withstood adjusting for effects of several sociodemographic covariates. These results offer confirmation of prior studies using smaller samples or non-population-based designs and with fewer mental health and religious indicators. They suggest that evidence for a salutary association between religious observance and mental health or psychological well-being among Israeli Jewish adults is consistent with findings in this literature for adherents to other faith traditions throughout the world.

Testing for sequential bias in school inspections

ABSTRACT Inspectors are tasked with judging the quality of provision based on visits to schools. They conduct these inspections sequentially, completing one before moving on to the next. However, empirical research in a range of settings outside education suggests that prior judgements in a sequence can influence subsequent judgements, despite being logically irrelevant. We investigate whether school inspectors in England display such sequential bias by testing whether they judge similar schools differently, depending on the judgements they reached in prior inspections. We find only limited evidence of sequential bias in primary school inspections. In particular, an inspector reaching an ‘Inadequate’ judgement in their previous inspection is associated with a 42 per cent reduction in the odds of reaching another ‘Inadequate’ judgement in their next inspection. Only around 5 per cent of inspection judgements result in an ‘Inadequate’ and we do not find consistent evidence of sequential bias at other grades, meaning this bias only affects a small minority of judgements. We also do not find the same results for secondary schools, albeit in a much smaller sample.

Investigation of perceived annoyance in indoor workplaces using short and ultra-short sound samples

Typically, metrics crucial for assessing sound quality are derived from high-quality audio samples obtained in controlled environments. However, due to the sensitive nature of workplace settings, recording audio samples on-site becomes impractical. Privacy emerges as a significant concern for all when collecting audio samples. Consequently, best practice would require that all analyses must occur either locally on a device used to record audio or in the cloud, utilizing a purely mathematical approach. The paper aims to formulate methodologies for determining psycho-acoustic sound quality metrics without the need to analyze audio data directly. This can be achieved by collecting and analyzing data in small batches. The variation of these metrics over these smaller samples can serve as an indicator of sound quality. Initiating the determination of values for psycho-acoustic sound quality metrics such as loudness (N), sharpness (S), roughness (R) and fluctuation strength (FS) in short and ultra-short batches, followed by monitoring their variation over an extended period (e.g., 5 minutes), provides additional insight into the sound characteristics of the space. Using the obtained psycho-acoustic sound quality metrics, we will explore the perceived annoyance among occupants through indoor soundscape assessments.

Obtaining High‐Resolution Magnetic Records From Speleothems Using Magnetic Microscopy

AbstractSpeleothems are mineral deposits capable of recording detrital and/or chemical remanent magnetization at annual timescales. They can offer high‐resolution paleomagnetic records of short‐term variations in Earth's magnetic field, crucial for understanding the evolution of the dynamo. Owing to limitations on the magnetic moment sensitivity of commercial cryogenic rock magnetometers (∼10−11 Am2), paleomagnetic studies of speleothems have been limited to samples with volumes of several hundreds of mm3, averaging tens to hundreds of years of magnetic variation. Nonetheless, smaller samples (∼1–10 mm3) can be measured using superconducting quantum interference device (SQUID) microscopy, with a sensitivity better than ∼10−15 Am2. To determine the application of SQUID microscopy for obtaining robust high‐resolution records from small‐volume speleothem samples, we analyzed three different stalagmites collected from Lapa dos Morcegos Cave (Portugal), Pau d'Alho Cave (Brazil), and Crevice Cave (United States). These stalagmites are representative of a range of magnetic properties and have been previously studied with conventional rock magnetometers. We show that by using SQUID microscopy we can achieve a five‐fold improvement in temporal resolution for samples with higher abundances of magnetic carriers (e.g., Pau d'Alho Cave and Lapa dos Morcegos Cave). In contrast, speleothems with low abundances of magnetic carriers (e.g., Crevice Cave) do not benefit from higher resolution analysis and are best analyzed using conventional rock magnetometers. Overall, by targeting speleothem samples with high concentrations of magnetic carriers we can increase the temporal resolution of magnetic records, setting the stage for resolving geomagnetic variations at short time scales.

A GWAS for grip strength in cohorts of children-Advantages of analysing young participants for this trait.

Grip strength (GS) is a proxy measure for muscular strength and a predictor for bone fracture risk among other diseases. Previous genome-wide association studies (GWASs) have been conducted in large cohorts of adults focusing on scores collected for the dominant hand, therefore increasing the likelihood of confounding effects by environmental factors. Here, we perform the first GWAS meta-analyses on maximal GS with the dominant (GSD) and non-dominant (GSND) hand in two cohorts of children (ALSPAC, N = 5450; age range = 10.65-13.61; Raine Study, N = 1162, age range: 9.42-12.38 years). We identified a novel significant association for GSND (rs9546244, LINC02465, p = 3.43e-08) and replicated associations previously reported in adults including with a HOXB3 gene marker that shows an expression quantitative trait locus (eQTL) effect. Despite a much smaller sample (~3%) compared with the UK Biobank we replicated correlation analyses previously reported in this much larger adult cohort, such as a negative correlation with coronary artery disease. Although the results from the polygenic risk score (PRS) analyses did not survive multiple testing correction, we observed nominally significant associations between GS and risk of overall fracture, as previously reported, as well ADHD which will require further investigations. Finally, we observed a higher SNP-heritability (24%-41%) compared with previous studies (4%-24%) in adults. Overall, our results suggest that cohorts of children might be better suited for genetic studies of grip strength, possibly due to the shorter exposure to confounding environmental factors compared with adults.

A Distance Transformation Deep Forest Framework With Hybrid-Feature Fusion for CXR Image Classification.

Detecting pneumonia, especially coronavirus disease 2019 (COVID-19), from chest X-ray (CXR) images is one of the most effective ways for disease diagnosis and patient triage. The application of deep neural networks (DNNs) for CXR image classification is limited due to the small sample size of the well-curated data. To tackle this problem, this article proposes a distance transformation-based deep forest framework with hybrid-feature fusion (DTDF-HFF) for accurate CXR image classification. In our proposed method, hybrid features of CXR images are extracted in two ways: hand-crafted feature extraction and multigrained scanning. Different types of features are fed into different classifiers in the same layer of the deep forest (DF), and the prediction vector obtained at each layer is transformed to form distance vector based on a self-adaptive scheme. The distance vectors obtained by different classifiers are fused and concatenated with the original features, then input into the corresponding classifier at the next layer. The cascade grows until DTDF-HFF can no longer gain benefits from the new layer. We compare the proposed method with other methods on the public CXR datasets, and the experimental results show that the proposed method can achieve state-of-the art (SOTA) performance. The code will be made publicly available at https://github.com/hongqq/DTDF-HFF.

Discontinuous Distribution of Test Statistics Around Significance Thresholds in Empirical Accounting Studies

ABSTRACTExamining test statistics from articles in six leading accounting journals, we detect discontinuities in their distributions around conventional significance thresholds (p‐values of 0.05 and 0.01) and find an unusual abundance of test statistics that are just significant. Further analysis reveals that these discontinuities are more prominent in studies with smaller samples and are more salient in experimental than in archival studies. The discontinuity discrepancy between experimental and archival studies relates to several proxies for researcher degrees of freedom. Nevertheless, this evidence does not imply that experimental research is more prone to questionable research practices than archival studies. Overall, our findings speak to the concern of whether accounting researchers could exercise undisclosed discretion to obtain and report statistically significant results. Based on our results, a healthy skepticism of some just‐significant test statistics is warranted.

Runx2 gene single nucleotide polymorphism in Class II and Class III malocclusions

To assess the prevalence of RUNX2 gene polymorphism in skeletal class II and class III malocclusions. : Unstimulated salivary samples of 36 patients (18- 30 years of age group), comprising 18 with skeletal class II and 18 with skeletal class III were collected from a tertiary care hospital in Mangalore. Salivary DNA samples were collected and analyzed using Sanger sequencing. Digital tracing was performed on lateral cephalometric radiographs by using AutoCAD software for digitization to assess the anterio-posterior and vertical relationship of the maxillary and mandibular arch.When polymorphism of 36 samples comprised of 18 Class II and 18 Class III were assessed, 83.3% Class III malocclusion and 5.6% Class II showed RUNX2 gene polymorphism in the population. Chi Square test which indicated that the results are statistically significant in Class III malocclusion for RUNX2 single nucleotide polymorphism (p<0.001). RUNX2 gene polymorphism was statistically significant in skeletal Class III malocclusion when compared to skeletal Class II malocclusion. This is a preliminary study done on a smaller sample, we need a larger sample size to confirm our findings.

Prevalence and characteristics of people with a high body mass index across the kidney disease spectrum: a population-based cohort study

The prevalence of obesity is growing globally and has major health implications, particularly for those with chronic kidney disease (CKD). People with obesity have a higher risk of CKD progression and face barriers to transplantation. Studies on the epidemiology and outcomes of obesity in the Canadian CKD population are lacking. This population-based cohort study included adults aged 18 and over with a hospital encounter in London, Ontario, Canada from 2010 to 2019 where height and weight were recorded. They were stratified into CKD stages 1-5 (by estimated glomerular filtration rate (eGFR)), dialysis or renal transplant status and by body mass index (BMI) using Canada Obesity Guidelines. Outcomes included prevalence of BMIs by CKD stage, and CKD progression and transplant outcomes across BMI classes. Our cohort included 198,151 patients. The prevalence of BMI ≥30 kg/m2 grew as eGFR declined (i.e., 37% in stage 1, 41.5% in stage 3b, 40.9% in stage 4) but fell in end-stages (i.e., 37.4% in Stage 5, 38.8% in dialysis, 38.5% in transplant recipients). CKD progression and kidney failure appeared more frequent in those with a BMI ≥30 kg/m2. In a smaller sample, we noted that end-stage patients with a BMI ≥30 kg/m2 were less frequently transplanted, but experienced post-transplant complications less often. This study revealed that high BMI is a prevalent issue in the Canadian CKD population and may influence kidney outcomes and transplant candidacy. This data will help inform clinical trials to create and study weight loss interventions for those with CKD and obesity.

Microfluidics and Chip Development

During the course of the summer, I had the privilege to work with Dr. Carlos Escobedo and his team of researchers on the topics of microfluidics and Lab-On-Chip (LOC) technology. Microfluidics is a branch of fluid dynamics which utilizes small volumes of fluid to perform tests under ideal conditions, and LOC is the process of using microfluidics for experiments in small-scale environments. I participated in two LOC projects, the first for bacterial analysis and the second for microplastic separation. The goal of the first project was to observe if Vibrio Cholerae bacteria was attracted to a variety of chemo attractants. To observe this interaction under microfluidic conditions, we developed a chip which when flooded with chemoattractant trapped a portion in the chip. We could then remove the non-entrapped chemoattractant from the sides and refill the chip with bacteria. Observations of the bacteria’s movement were then taken using a microscope attached to a digital camera. The second project focused on microplastics, which are plastic particulates under 5mm in diameter, our smallest sample being 10μm. Due to their size standard filtering techniques were ineffective at separating them, which led to us using Deterministic Lateral Displacement (DLD). DLD utilizes an array of pillars to create spots of changing pressure for passing particles. The array is designed so larger particles are unaffected while smaller particulates will be redirected and collected separately. To arrange the plastics into their types, a centrifugal design was used. This design functions similarly to a centrifuge, which by rapidly spinning a substance separates out materials based on density. The chip works under a similar theory, but instead uses a spiral channel to force the particles in a repeated circular spinning motion. The particles then exit with differing directionalities based on where they were in the channel, allowing for collection.

The efficacy of cognitive behavioural therapy for depression and anxiety in multiple sclerosis: A systematic review and meta-analysis

Background: Adults with multiple sclerosis (MS) frequently experience symptoms of depression and anxiety, which pose significant challenges. However, psychological support for these symptoms remains a major unmet healthcare need.Objectives: To inform the evidence base for the psychological management of adults with MS, this study examined the efficacy of cognitive behavioural therapy (CBT) interventions for improving symptoms of depression and anxiety. CBT interventions teach skills for improving the relationships between an individual's thoughts, feelings, and/or behaviours. The study also examined the role of intervention and study characteristics as moderators of treatment effects.Methods: Medline, Embase, PsycINFO, and Cochrane Central Register of Controlled Trials were searched up to August 2024 for randomised control trials.Results: A meta-analysis of 15 clinical trials (1508 participants) was conducted, which found a medium significant treatment effect size for depression symptoms (g = 0.59, 95 % Confidence Interval [CI] [0.38, 0.80]) and a small significant treatment effect size for anxiety symptoms (g = 0.38 95 % CI [0.19, 0.57]). Moderator analyses revealed treatment effects for anxiety, but not depression, were significantly larger for studies conducted in non-Western countries compared to Western countries, and for those with smaller sample sizes.Conclusions: CBT-based interventions appear efficacious for the management of depression and anxiety symptoms in adults with MS. However, future clinical trials with larger samples and more rigorous methodology are warranted. Further examination of intervention characteristics, including ways in which CBT is tailored and how this relates to outcomes, may help to refine interventions for people with MS.

Genotype and Phenotype Association Analysis Based on Multi-omics Statistical Data

Background: When using clinical data for multi-omics analysis, there are issues such as the insufficient number of omics data types and relatively small sample size due to the protection of patients' privacy, the requirements of data management by various institutions, and the relatively large number of features of each omics data. This paper describes the analysis of multi-omics pathway relationships using statistical data in the absence of clinical data. Methods: We proposed a novel approach to exploit easily accessible statistics in public databases. This approach introduces phenotypic associations that are not included in the clinical data and uses these data to build a three-layer heterogeneous network. To simplify the analysis, we decomposed the three-layer network into double two-layer networks to predict the weights of the inter-layer associations. By adding a hyperparameter β, the weights of the two layers of the network were merged, and then k-fold cross-validation was used to evaluate the accuracy of this method. In calculating the weights of the two-layer networks, the RWR with fixed restart probability was combined with PBMDA and CIPHER to generate the PCRWR with biased weights and improved accuracy. Results: The area under the receiver operating characteristic curve was increased by approximately 7% in the case of the RWR with initial weights. Conclusion: Multi-omics statistical data were used to establish genotype and phenotype correlation networks for analysis, which was similar to the effect of clinical multi-omics analysis.

Influence of stress-specific interventions on biomarker levels and cognitive function in cancer patients: Systematic review and meta-analysis.

Cancer patients' psycho-physiological health is seriously affected by long-term exposure to stress. Many studies have explored the impact of stress-specific interventions on cancer patients' biomarker levels and cognitive functions. However, the current research findings are inconsistent, and their statistical power is limited by the small samples. Therefore, we conducted this meta-analysis to verify the effect of stress-specific interventions on cancer patients. The literature involved nine databases from the inception until January 13, 2024, extracted 19 randomized controlled trials (RCTs). Review Manager (RevMan) 5.4 software was used to perform a meta-analysis, and the revised Cochrane risk of bias tool (RoB2) was utilized for quality evaluation. Nine RCTs were assessed as having a low risk of bias, and others had a moderate risk. The results showed that stress-specific interventions had beneficial effects on patients' subjective cognition but uncertain impacts on their executive function, tumour necrosis factor-α level, morning cortisol level, and no effect on cortisol at other times, interleukin (IL)-10, IL-8, IL-6, IL-1, and C-reactive protein. More rigorous studies are required to elucidate the influence of stress-specific interventions on biomarker levels. The potential mechanism by which stress-specific interventions affect the cancer patient's cognitive function remains unclear.

Eugenol, menthol and other flavour chemicals in kreteks and ‘white’ cigarettes purchased in Indonesia

BackgroundFlavoured tobacco products are not restricted in Indonesia, a country with about 68 million adults who smoke. Most use clove-mixed tobacco cigarettes (‘kreteks’); non-clove (‘white’) cigarettes are also available. Although...

Estimating Addiction-Related Brain Connectivity by Prior-Embedding Graph Generative Adversarial Networks.

The study of nicotine addiction mechanism is of great significance in both nicotine withdrawal and brain science. The detection of addiction-related brain connectivity using functional magnetic resonance imaging (fMRI) is a critical step in study of this mechanism. However, it is challenging to accurately estimate addiction-related brain connectivity due to the low-signal-to-noise ratio of fMRI and the issue of small sample size. In this work, a prior-embedding graph generative adversarial network (PG-GAN) is proposed to capture addiction-related brain connectivity accurately. By designing a dual-generator-based scheme, the addiction-related connectivity generator is employed to learn the feature map of addiction connection, while the reconstruction generator is used for sample reconstruction. Moreover, a bidirectional mapping mechanism is designed to maintain the consistency of sample distribution in the latent space so that addiction-related brain connectivity can be estimated more accurately. The proposed model utilizes prior knowledge embeddings to reduce the search space so that the model can better understand the latent distribution for the issue of small sample size. Experimental results demonstrate the effectiveness of the proposed PG-GAN.

Heart Rate Variability Biofeedback as a Treatment for Military PTSD: A Meta-Analysis.

Emerging research has provided tentative support for the use of heart rate variability biofeedback (HRVB) as a treatment for several psychological disorders, with meta-analyses providing compelling evidence for HRVB as a promising treatment for anxiety, depression, and PTSD. Given the prevalence of PTSD in military veterans and the comparatively lower benefit and higher attrition rate of traditional psychological treatment for PTSD relative to civilian counterparts, it is important to examine complementary and alternative treatment approaches such as HRVB in this population. Although studies of HRVB for PTSD have been conducted with military veterans, they have involved relatively small sample sizes, limiting interpretation. To address this, the current article presents a comprehensive meta-analysis, consolidating existing literature to more accurately evaluate the efficacy of HRVB in reducing PTSD symptoms within military populations. This meta-analysis was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines, and our protocol was registered with PROSPERO to increase review transparency. A literature search of HRVB interventions was conducted using PubMed, PsycINFO, Military Database, PTSDPubs, and EBSCO's Psychological and Behavioral Sciences Collection. Five studies met eligibility criteria, providing a combined sample size of 95 military services members. For all studies, effect sizes were negative, indicating a reduction in PTSD symptoms. Effect sizes ranged from -1.614 to -0.414, resulting in an overall moderate to large mean effect for HRVB (Hedges's g = -0.557; 95% confidence interval = -0.818 to -0.296; P < .001). Additionally, cumulative attrition was 5.8%, significantly lower than commonly reported rates for evidence-based treatments (16%-36%). The present study is the first meta-analysis to examine HRVB as a treatment for military service members with PTSD. Results indicate that HRVB may be a viable treatment approach to reduce PTSD symptomatology. Low attrition rates, ease of accessibility, and favorable participant outlook serve as additional benefits for the use of HRVB.

Pharmacological interventions for pruritus in adult palliative care patients.

Pharmacological interventions for pruritus in adult palliative care patients.

The Impact of Nuclear Energy Consumption, Green Technological Innovation, and Trade Openness on the Sustainable Environment in the USA

Nuclear energy, renewable energy, and alternative energy sources are all crucial for sustainable green energy. However, the existing literature often needs to pay more attention to the role of nuclear energy in achieving sustainable development goals. This study analyzes the impact of green technological innovation, nuclear energy consumption, and trade openness on environmental quality in the US. The authors used the ARDL bounds to identify cointegration relationships, which is appropriate for this study’s dataset as it works well with smaller samples. They also used the Toda–Yamamoto causality test to examine causal links. The ARDL cointegration results indicate a significant long-term relationship between CO2 emissions, green technological innovation, nuclear energy consumption, and trade openness. Green technological innovation has a negative impact on CO2 emissions. Higher nuclear energy consumption is associated with lower CO2 emissions, while greater trade openness is associated with higher CO2 emissions, although these effects are less certain. The results suggest promoting green technological innovation and nuclear energy can be effective strategies for reducing CO2 emissions, while the impact of trade openness requires careful consideration due to its potential to increase emissions.

The sodium correction factor for dogs undergoing treatment for a hyperglycemic crisis is a 1.6-mEq/L decrease in sodium per 100-mg/dL increase in glucose.

To determine the sodium correction factor for clinical use in hyperglycemic diabetic dogs. Retrospective analysis of 76 hospitalization episodes from 67 different dogs presenting to the University of Georgia Veterinary Teaching Hospital between January 1, 2015, and January 1, 2023. For each hospitalization episode, paired blood sodium and glucose concentration measurements were recorded from the time of presentation until glucose concentration was ≤ 201 mg/dL. Therapies administered, primary diagnosis, and concurrent diseases were also recorded for each episode. A linear mixed model was used to determine the sodium correction factor per 100-mg/dL increase in glucose. Piecewise linear mixed models were also constructed for blood glucose measurements ≤ 400 mg/dL and > 400 mg/dL to explore potential correction factor differences between low and high glucose concentrations. A sodium correction factor of a 1.6-mEq/L (95% CI, 1.3 to 1.9 mEq/L) decrease in sodium concentration per 100-mg/dL increase in blood glucose concentration was calculated. Differences in the correction factor between conditions of low and high glucose concentrations could not be determined due to a small sample size of blood glucose values > 400 mg/dL. Most dogs received similar treatments throughout the study period, including balanced isotonic crystalloids (97% [74/76]), electrolyte supplementation (84% [64/76]), and regular insulin (97% [74/76]). Almost all patients (93% [71/76]) had 1 or more concurrent diseases. A sodium correction factor of 1.6 mEq/L (decrease in sodium per 100-mg/dL increase in glucose) is recommended for clinical use in hyperglycemic diabetic dogs.