Large Population Research Articles

Cardio-pulmonary exercise testing in adult congenital heart patients: a new data-focused approach to predict mortality

Abstract Background/Introduction The cardio-pulmonary exercise test (CPET) has been a pivotal tool for functional and prognostic evaluation in adults with congenital heart disease (ACHD). During a routine CPET test, a myriad of variables are collected reflecting the cardiovascular, pulmonary, and skeletal muscle systems. However, clinicians typically use only a few easily and accessible variables to establish prognosis, which can come at an accuracy cost. Machine learning algorithms have undergone significant development in recent years and have found applications in the medical field. One of their main advantages is the ability to handle a large number of variables and extract information from their various combinations, while excluding redundant data, thus offering a higher level of prediction accuracy. Purpose Our objective was to develop a machine learning model to predict death during follow-up in a large population of ACHD patients who have undergone routine CPET in a large-volume single specialist centre. Methods All available CPET studies for adult ACHD patients (age > 15 years) performed from December 1999 to December 2021 at our centre were included, and all standard available variables were extracted. The primary outcome was all-cause mortality since the CPET, collected up to November 2023. Data exploration, data cleaning, and feature engineering steps were conducted using Python (v3.8). Continuous variables were standardised. The supervised machine learning algorithm XGBoost was used for classification (all-cause mortality), with the best hyperparameters selected through cross-validation. For the final model, a feature importance analysis based on permutation techniques was used to explore the variables with more impact on model accuracy. Results A total of 6361 studies were included, with median age of 31 years (IQR 23-43), 56% male. During follow-up, a total of 491 deaths were recorded. Of available demographic, clinical and exercise parameters (n=129 variables), 21 were deemed sufficient in terms of completeness, absence of significant correlation and clinically relevant for the subsequent analysis. These included demographic variables (age and sex) and CPET variables (peak VO2, FEV1, peak heart rate, exercise time, etc.) and were used to train the model. The accuracy of the model in predicting death after CPET in the test set had an accuracy of 93.5% and an area under the ROC curve (AUC) of 85.0% (Figure1). The parameters with the highest relative feature importance were FEV1, body mass index and percent predicted peak VO2 (Figure 2). Conclusions Machine learning models can be effectively employed in specialised cardiac populations, such as ACHD, potentially providing a high level of prediction accuracy by efficiently harnessing the potential of available data. However, its applicability to mortality prediction for ACHD patients requires further external validation.ROC curve AUC for the model predictionsFeature importance using permutation

Detecting Unrecognized Dementia Using Deep Learning Methods with Korean National Claims Data

Abstract Background Dementia is one of the leading causes of death in elderly people. In Korea, the government supports dementia screening for people aged 60 and older, but it is not a population-based organized screening program. It is difficult to achieve early diagnosis and early treatment. The objective of this study is to detect unrecognized dementia using Korean National Claims Data for early diagnosis. Methods This study used the National Health Insurance Claims data in Korea. The case group is the new dementia visit as an unrecognized group, while the control group was randomly selected from the general population without dementia. The predictors included health utilization, socioeconomic and demographic, procedure codes, diagnostic codes and health screenings data. The health utilization variables included length of stay, the number of outpatient visits, health expenditures and other encounter information. All medical utilization data was aggregated monthly. In the case group, 12 months of data from 6-month or 2-years before the onset of dementia were used. In the control group, 12 months of data from randomly selected time point were included. Transformer, embedding methods, and Time2Vec were used as the deep learning methods. This study included 453,306 incidents of dementia, representing almost all cases reported from 2010 to 2019 in Korea. The control group consisted of 669,873. Results After training the deep learning prediction model, the AUC for 6-month dementia prediction on the test dataset was 0.87, and for 2-year dementia prediction, it was 0.76. The most important variables were health utilization variables, especially health expenditures. The health utilization trajectories of the case group were significantly different from those of the control group. Conclusions Based on the claims data, we could detect unrecognized dementia case. We can extend the model to other chronic disease such as cancer and stroke, which are significant burden of disease. Key messages • Screening in healthcare facilities or using lab test results would be more accurate, but it would be difficult to apply to a large population due to the cost-effectiveness and timeliness constraints. • On the other hand, the detection model using the existing claims data would be helpful to to develop cost-effective mass screening program. It can cover the weakness of current screening program.

COMPARISON OF SURGICAL SITE INFECTION IN PATIENTS UNDERGOING SKIN CLOSURE WITH STAPLES VS. SUTURES IN CLEAN ELECTIVE SURGERIES

Thyroidectomy is a common surgical procedure with various techniques for wound closure, including dermal staples and intradermal suturing. Each method has potential advantages and disadvantages, particularly in terms of wound complications, cosmetic outcomes, and postoperative pain. Understanding which technique offers better outcomes in these areas can guide surgeons in selecting the most appropriate method for skin closure after thyroidectomy. Objective: To compare wound complications, cosmetic outcomes, and pain scores between skin closure with dermal staples and intradermal sutures in patients undergoing thyroidectomy. Methods: A prospective study was conducted in the Surgical Department of Sheikh Zayed Hospital, Lahore, from August 2023 to August 2024. The study included 100 adult patients undergoing thyroidectomy for thyroid disease. The patients were randomly divided into two groups: Group A (n=50) received wound closure with dermal staples, and Group B (n=50) received intradermal suturing. Postoperative assessments were conducted at 1, 4, 12, and 24 weeks to evaluate wound complications, cosmetic outcomes, and pain scores. Cosmetic outcomes were measured using the Stony Brook Scar Evaluation Scale and Manchester Scar Scale. Pain was assessed using the Visual Analog Scale (VAS). Results: No surgical site infections were reported in either group. At the 24-week follow-up, cosmetic outcomes measured by the Stony Brook Scar Evaluation Scale were significantly better in Group A (4.12 ± 1.0) compared to Group B (3.32 ± 1.17) (p=0.027). Similarly, the Manchester Scar Scale score was higher in Group A (7.83 ± 1.34) than in Group B (9.20 ± 2.26) (p=0.033), indicating better cosmesis with staples. However, pain scores were significantly higher in Group A than in Group B both immediately after surgery and at the 4- and 12-week follow-ups. Conclusion: The use of dermal staples in thyroidectomy demonstrated better cosmetic outcomes and wound healing compared to intradermal suturing. However, patients who received staples experienced significantly more postoperative pain. While dermal stapling is a safe and effective alternative for skin closure, further studies with larger populations are necessary to corroborate these findings and guide clinical practice.

Artificial Intelligence-Based Sentinel Lymph Node Metastasis Detection in Cervical Cancer.

Background/objectives: Pathological ultrastaging, an essential part of sentinel lymph node (SLN) mapping, involves serial sectioning and immunohistochemical (IHC) staining in order to reliably detect clinically relevant metastases. However, ultrastaging is labor-intensive, time-consuming, and costly. Deep learning algorithms offer a potential solution by assisting pathologists in efficiently assessing serial sections for metastases, reducing workload and costs while enhancing accuracy. This proof-of-principle study evaluated the effectiveness of a deep learning algorithm for SLN metastasis detection in early-stage cervical cancer. Methods: We retrospectively analyzed whole slide images (WSIs) of hematoxylin and eosin (H&E)-stained SLNs from early-stage cervical cancer patients diagnosed with an SLN metastasis with either H&E or IHC. A CE-IVD certified commercially available deep learning algorithm, initially developed for detection of breast and colon cancer lymph node metastases, was employed off-label to assess its sensitivity in cervical cancer. Results: This study included 21 patients with early-stage cervical cancer, comprising 15 with squamous cell carcinoma, five with adenocarcinoma, and one with clear cell carcinoma. Among these patients, 10 had macrometastases and 11 had micrometastases in at least one SLN. The algorithm was applied to evaluate H&E WSIs of 47 SLN specimens, including 22 that were negative for metastasis, 13 with macrometastases, and 12 with micrometastases in the H&E slides. The algorithm detected all H&E macro- and micrometastases with 100% sensitivity. Conclusions: This proof-of-principle study demonstrated high sensitivity of a deep learning algorithm for detection of clinically relevant SLN metastasis in early-stage cervical cancer, despite being originally developed for adenocarcinomas of the breast and colon. Our findings highlight the potential of leveraging an existing algorithm for use in cervical cancer, warranting further prospective validation in a larger population.

Characterization of the wheat-tetraploid Thinopyrum elongatum 7E(7D) substitution line with Fusarium head blight resistance

BackgroundFusarium head blight (FHB), a devastating disease of wheat production, is predominantly elicited by Fusarium graminearum (Fg). The tetraploid Thinopyrum elongatum is a tertiary gene resource of common wheat that possesses high affinity and displays high resistance traits against multiple biotic and abiotic stress. We aim to employ and utilize the novel FHB resistance resources from the wild germplasm of common wheat for breeding.ResultsDurum wheat-tetraploid Th. elongatum amphiploid 8801 was hybridized with common wheat cultivars SM482 and SM51, and the F5 generation was generated. We conducted cytogenetically in situ hybridization (ISH) technologies to select and confirm a genetically stable 7E(7D) substitution line K17-1069-5, which showed FHB expansion resistance in both field and greenhouse infection experiments and displayed no significant disadvantage in agronomic traits compared to their common wheat parents in the field. The F2 segregation populations (K17-1069-5 × SM830) showed that the 7E chromosome conferred dominant FHB resistance with dosage effect. We developed 19 SSR molecular markers specific to chromosome 7E, which could be conducted for genetic mapping and large breeding populations marker-assisted selection (MAS) during selection procedures in the future. We isolated a novel Fhb7 allele from the tetraploid Th. elongatum chromosome 7E (Chr7E) using homology-based cloning, which was designated as TTE7E-Fhb7.ConclusionsIn summary, our study developed a novel wheat-tetraploid Thinopyrum elongatum 7E(7D) K17-1069-5 substitution line which contains stable FHB resistance.

Economic influence of prosperity gospel on individual followers in neo-Pentecostal movements in Karingani Ward Tharaka Nithi County, Kenya

The study sought to investigate how prosperity gospel influences the economic aspect of its followers in neo-Pentecostal movements in Karingani Ward Tharaka Nithi County, Kenya. In Kenya, Neo-Pentecostal movements are growing and spreading from urban to rural areas, as witnessed in Karingani Ward, Tharaka Nithi County, Kenya. There has been an increase in self-founded churches, commonly known as charismatic movements, over the past decade. The Functionalism Theory guided the study in analysing the prosperity gospel's influence on its followers' economic aspect. The theory indicates that religion is a social influencer that leads to changes in behaviour and perception or worldview that are essential to economic growth. The study applied the descriptive survey design. Yamane’s formula was applied to obtain a sample size of 288 respondents. In addition, six pastors were selected from the churches; the total sample was 294 respondents. In the six selected churches, a larger population was between (20-50 years); the majority were women and indicated to be small business owners and employed in the private sector. The research instruments utilised were questionnaires, interviews, and focused group discussions. The study's findings revealed that prosperity teachings in Neo-Pentecostal movements positively influenced its followers. Prosperity teaching with biblical grounding had influenced adherents in these movements to have financial, investment, and entrepreneurial abilities through seminars, idea sharing, and continuous assistance from members, which have impacted their followers to experience social status mobility. This paper recommends a future study on how perceived YouTube or social media incomes can benefit all adherents.

Ruminant microbiome data are skewed and unFAIR, undermining their usefulness for sustainable production improvement

The ruminant microbiome plays a key role in the health, feed utilization and environmental impact of ruminant production systems. Microbiome research provides insights to reduce the environmental footprint and improve meat and milk production from ruminants. However, the microbiome composition depends on the ruminant species, habitat and diet, highlighting the importance of having a good representation of ruminant microbiomes in their local environment to translate research findings into beneficial approaches. This information is currently lacking. In this study, we examined the metadata of farmed ruminant microbiome studies to determine global representativeness and summarized information by ruminant species, geographic location, body site, and host information. We accessed data from the International Nucleotide Sequence Database Collaboration via the National Center for Biotechnology Information database. We retrieved 47,628 sample metadata, with cattle accounting for more than two-thirds of the samples. In contrast, goats, which have a similar global population to cattle, were underrepresented with less than 4% of the total samples. Most samples originated in Western Europe, North America, Australasia and China but countries with large ruminant populations in South America, Africa, Asia, and Eastern Europe were underrepresented. Microbiomes from the gastrointestinal tract were the most frequently studied, comprising about 87% of all samples. Additionally, the number of samples from other body sites such as the respiratory tract, milk, skin, reproductive tract, and fetal tissue, has markedly increased over the past decade. More than 40% of the samples lacked basic information and many were retrieved from generic taxonomic classifications where the ruminant species was manually recovered. The lack of basic information such as age, breed or sex can limit the reusability of the data for further analysis and follow-up studies. This requires correct taxonomic assignment of the ruminant host and basic metadata information using accepted ontologies adapted to host-associated microbiomes. Repositories should require this information as a condition of acceptance. The results of this survey highlight the need to encourage studies of the ruminant microbiome from underrepresented ruminant species and countries worldwide. This shortfall in information poses a challenge for the development of microbiome-based strategies to meet sustainability requirements, particularly in areas with expanding livestock production systems.

Population of excited levels of Fe+, Ni+, and Cr+ in exocomets’ gaseous tails

The star β Pictoris is widely known for harbouring a large population of exocomets, which create variable absorption signatures in the stellar spectrum as they transit the star. Although the physical and chemical properties of these objects have long been elusive, the recently developed exocomet curve of growth technique has, for the first time, enabled estimates of exocometary column densities and excitation temperatures, based on absorption measurements in mutliple spectral lines. Using this new tool, we present a refined study of a β Pic exocomet observed on December 6, 1997 with the Hubble Space Telescope. We first show that the comet’s signature in Fe II lines is well explained by the transit of two gaseous components, with different covering factors and opacities. Then, we show that the studied comet is detected in the lines of other species, such as Ni II and Cr II. These species are shown to experience similar physical conditions as Fe II (same radial velocity profiles and same excitation temperatures), hinting that they are well mixed. Finally, using almost 100 Fe II lines rising from energy levels between 0 and 33 000 cm–1, we derive the complete excitation diagram of Fe+ in the comet. The transiting gas is found to be populated at an excitation temperature of 8190 ± 160 K, very close to the stellar effective temperature (8052 K). Using a model of radiative and collisional excitation, we show that the observed excitation diagram is compatible with a radiative regime, associated with a close transit distance (≤60 R⋆ ∼ 0.43 au) and a low electronic density (≤107 cm–3). In this regime, the excitation of Fe+ is controlled by the stellar flux, and does not depend on the local electronic temperature or density. These results allow us to derive the Ni+/Fe+ and Cr+/Fe+ ratios in the December 6, 1997 comet, at 8.5 ± 0.8 ⋅ 10–2 and 1.04 ± 0.15 ⋅10–2, respectively, close to solar abundances.

Phenotype in Individuals with Heterozygous Rare Variants in LIPC Encoding Hepatic Lipase.

Hepatic lipase deficiency is a rare genetic condition caused by biallelic loss-of-function variants in the LIPC gene encoding hepatic lipase. These variants reduce or abolish the protein's lipolytic activity, resulting in elevated plasma lipids. The condition is classified as autosomal recessive, since dyslipidemia is inconsistently observed in heterozygous patients with only one LIPC variant. However, this has been concluded from historical studies encompassing a few families and having very small sample sizes. Here, we conduct a retrospective chart review of 46 heterozygous subjects, each harboring one rare pathogenic LIPC variant. We compare plasma levels of total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), triglycerides, and apolipoprotein B to those of matched controls without LIPC variants. Variant pathogenicity is classified according to the guidelines of the American College of Medical Genetics and Genomics. We observe that levels of total cholesterol, LDL-C, and triglycerides are significantly elevated in the LIPC variant heterozygotes, but HDL-C and apolipoprotein B are not. When filtering solely with respect to pathogenic or likely pathogenic variants, all lipid variables emerge as significantly elevated compared to controls. Thus, hepatic lipase deficiency may not necessarily be a recessive condition, but perhaps semi-dominant since individuals with one variant are phenotypically distinct from the controls. These hypothesis-generating findings regarding LIPC genetic variations observed in a clinical cohort should be evaluated in larger populations and databases.

Small Left Ventricular Chamber Size and Mortality in a Large General Population

Enlargement of the left ventricle (LV) is an important marker of adverse cardiac remodeling and poor prognosis. Previous studies demonstrated increased cardiovascular risk in small subsets of patients with small LV chamber size, however, the prognostic implications of small chamber size in a general population remains unclear. The objective of this study was to examine the prognosis of a small LV chamber in a large general cohort. All consecutive subjects that underwent echocardiography examinations from 2011 to 2023 were retrieved for analysis. Small chamber size was defined as end-diastolic diameter less than 42 mm for men and 37.8 mm for women as per ASE guidelines. The primary endpoint for the study was all-cause mortality. 46,529 subjects (mean age 60 ± 19 years, 56% males) were included of whom 3,787 had small LV chamber size. Clinical variables associated with small chamber included increasing age and lower BSA. Echocardiographic variables included higher relative wall thickness, and E/e' ratio. On multivariable analysis, the presence of a small LV was significantly associated with mortality (HR 1.34 with 95% CI 1.22-1.46; p <0.001). This finding was significant in both older (over 65 years) (HR 1.30 95% CI 1.19-1.41; p <0.001) and younger (HR 2.09 95% CI 1.81-2.41; p <0.001) subjects and in both males and females. In conclusion, in this retrospective large cohort study, small LV chamber size was significantly associated with mortality in a broad range of patients. Further study is necessary to elucidate mechanisms and design preventive strategies.

Intra-individual Variability in Lipoprotein(a) Levels: Findings from a Large Academic Health System Population.

Lipoprotein(a) [Lp(a)] levels are known to be mainly genetically determined. However, only scarce data are available on the intra-individual variability of Lp(a) levels across time. We included adult patients (≥18 years old) who had baseline and follow-up Lp(a) measurements (between 1997 and 2024) with a minimum of one year apart. Patients were categorized into three groups as follows: normal (<30 mg/dL), borderline (30 to 50 mg/dL) and high Lp(a) (≥50 mg/dL). Multivariable logistic regression was conducted to assess the predictors of the intra-individual changes in Lp(a) ≥10 mg/dL. A total of 11,669 individuals (median age: 54 years, 60% males) were included in our analysis, with median time between measurements of 4.5 years (IQR: 2.2, 10.6). The median Lp(a) was 16 mg/dL (IQR: 7, 52) at baseline, compared with 15 mg/dL (IQR: 7, 52) at follow-up. At follow-up, 96.4% of individuals with normal Lp(a) and 89.9% with high Lp(a) remained in their categories, while 51.2% with borderline Lp(a) changed their category. Of the included population, 24.9% had an intra-individual Lp(a) change ≥10 mg/dL. Female sex (p <0.001), history of ASCVD (p=0.003), statin therapy (p=0.003) and elevated low-density lipoprotein cholesterol (LDL-C) levels ≥100 mg/dL (p <0.001) were significantly associated with higher odds of intra-individual Lp(a) changes ≥10 mg/dL. Lipoprotein(a) levels were generally stable over time; however, patients with borderline levels may require more than one Lp(a) measurement, especially if they are females, have a history of ASCVD, have elevated LDL-C levels or are on statins therapy.

Natural alleles of LEAFY and WAPO1 interact to regulate spikelet number per spike in wheat

Key messageSpecific combinations ofLFY andWAPO1 natural alleles maximize spikelet number per spike in wheat. Spikelet number per spike (SNS) is an important yield component in wheat that determines the maximum number of grains that can be formed in a wheat spike. In wheat, loss-of-function mutations in LEAFY (LFY) or its interacting protein WHEAT ORTHOLOG OF APO1 (WAPO1) significantly reduce SNS by reducing the rate of formation of spikelet meristems. In previous studies, we identified a natural amino acid change in WAPO1 (C47F) that significantly increases SNS in hexaploid wheat. In this study, we searched for natural variants in LFY that were associated with differences in SNS and detected significant effects in the LFY-B region in a nested association mapping population. We generated a large mapping population and confirmed that the LFY-B polymorphism R80S is linked with the differences in SNS, suggesting that LFY-B is the likely causal gene. A haplotype analysis revealed two amino acid changes P34L and R80S, which were both enriched during wheat domestication and breeding suggesting positive selection. We also explored the interactions between the LFY and WAPO1 natural variants for SNS using biparental populations and identified significant interaction, in which the positive effect of the 80S and 34L alleles from LFY-B was only detected in the WAPO-A1 47F background but not in the 47C background. Based on these results, we propose that the allele combination WAPO-A1-47F/LFY-B 34L 80S can be used in wheat breeding programs to maximize SNS and increase grain yield potential in wheat.

Development of a German version of a single-question restless legs syndrome screening questionnaire

Abstract Background The “Single Question for the Rapid Screening of Restless Legs Syndrome (RLS Single Question) ©” is a questionnaire specifically designed to screen for restless legs syndrome (RLS). This research article describes the process of development and cultural adaptation of the German version of the questionnaire. Objective The primary objective of this study was to create a culturally appropriate and linguistically precise tool for evaluating RLS symptoms within German-speaking populations. Materials and methods The translation process involved meticulous forward and backward translations coupled with cognitive interviews conducted with patients to ensure the linguistic accuracy and cultural relevance of the instrument. Results The resultant final version of the questionnaire demonstrated an optimal level of comprehension and is anticipated to serve as an asset for the early detection and effective management of RLS among individuals who speak German. Conclusion The study highlights the successful development of the RLS questionnaire for the German-speaking context. Patient involvement in cognitive interviews proves pivotal in resolving minor comprehension issues. Its successful adaptation underscores the significance of comprehensive translation in diverse linguistic and cultural contexts, ultimately enhancing patient care. Future research will explore the validation of the test in larger populations and its integration into holistic diagnostic strategies.

Latent dynamics of primary sensory cortical population activity structured by fluctuations in the local field potential.

As emerging technologies enable measurement of precise details of the activity within microcircuits at ever-increasing scales, there is a growing need to identify the salient features and patterns within the neural populations that represent physiologically and behaviorally relevant aspects of the network. Accumulating evidence from recordings of large neural populations suggests that neural population activity frequently exhibits relatively low-dimensional structure, with a small number of variables explaining a substantial fraction of the structure of the activity. While such structure has been observed across the brain, it is not known how reduced-dimension representations of neural population activity relate to classical metrics of "brain state," typically described in terms of fluctuations in the local field potential (LFP), single-cell activity, and behavioral metrics. Hidden state models were fit to spontaneous spiking activity of populations of neurons, recorded in the whisker area of primary somatosensory cortex of awake mice. Classic measures of cortical state in S1, including the LFP and whisking activity, were compared to the dynamics of states inferred from spiking activity. A hidden Markov model fit the population spiking data well with a relatively small number of states, and putative inhibitory neurons played an outsize role in determining the latent state dynamics. Spiking states inferred from the model were more informative of the cortical state than a direct readout of the spiking activity of single neurons or of the population. Further, the spiking states predicted both the trial-by-trial variability in sensory responses and one aspect of behavior, whisking activity. Our results show how classical measurements of brain state relate to neural population spiking dynamics at the scale of the microcircuit and provide an approach for quantitative mapping of brain state dynamics across brain areas.

Genetic Characterization and Breeding Habitats of Black Fly (Diptera, Simuliidae) Vector Species in Laos

Genetic diversity and ecology are two important aspects of vector species crucial to a full understanding of disease epidemiology. In this study, we examined genetic diversity, genetic structure and the physiochemical parameters of the breeding habitats of the two significant black fly vector species, Simulium chumpornense Takaoka and Kuvangkadilok and S. nodosum Puri, from Laos. Genetic diversity of S. chumpornense in Laos was relatively high with maximum genetic divergence of 3.05% but no significant genetic differentiation between populations. Comparisons with conspecific populations from Thailand also found no genetic differentiation between the two countries. This possibly related to the recent history of this species, as a very recent (31,000 years ago) historical population expansion was detected. Physicochemical parameters of the breeding habitats suggest the ability to utilize diverse stream sizes from small flows (1 m wide) to huge rivers (290 m or more wide). Populations of S. nodosum from Laos had low genetic diversity with maximum genetic divergence of 2.56% and no genetic structuring among populations. Comparisons with those reported from other countries revealed five genetically divergent lineages (I–V) with minimum genetic divergence of 1.36%. The majority (42 of 52) of specimens from Laos belonged to lineage I and the remaining (10) comprised lineage II. Lineage I is the largest and representative of specimens from Thailand, Myanmar, Vietnam, Taiwan and Laos. Population history analysis revealed that lineage I had undergone recent demographic expansion dating back to 7000 years ago. This very recent population expansion resembles others reported from Thailand and possibly indicates a response to increasing human and domestic animals following the agricultural revolution. Breeding sites of S. nodosum are diverse in respect to elevation, velocity, water conductivity and streambed particle size. The ability to utilize a wide variety of breeding sites could promote the production of a large adult population, which can be a pest for humans and other animals.

Cultivating Digital Skills: Assessing Trainee Digital Skills and Individual Needs

It is widely recognised that having applicable digital skills is crucial to a lot of professions and is highly relevant to economic growth and digital transformation. Additionally, a lot of digital training does not consider, the specific needs of the individual. As such, this paper presents an adaption for means of digital skills assessment and training readiness, and practical skills appraisals, which allows training to be modified to individual needs. This paper focuses on a skills' assessments (appraisals) for working professionals that are not in traditionally IT specialist roles such as physio therapists and food technicians, specifically in how working professionals can be assessed and better prepared for digital upskilling. An adapted framework is motivated by using concepts of digital skills' assessment by Van Laar et al. (2018), which includes adapting their established set of measures for 21st century Digital skills. The results and findings, to date, are based upon twelve skills appraisals and six short training sessions, across six participants. Resulting in qualitative data in the form of researcher observations and participant narrations over skill-based activities with non-IT based professionals. Participants were recruited primarily from a regional skills support scheme focused upon digital skills' development, for people in employment. The aims of this paper are to report the findings of active research and to provide initial insights regarding strategies for digital trainers. The suggested approaches are intended to highlight areas of interest and focus for trainees. These approaches should benefit skills development and delivery for a large population of non-IT based professionals.

67 A population-based cohort study of endocrine outcomes within the first 5 years of life in children born preterm

Abstract Background Preterm birth (&amp;lt;37 weeks’ gestational age [GA]) occurs in 8% of live births in Canada. While advancements in neonatal medicine have led to increased survival in preterm births, infants born preterm continue to sustain short- and long-term health sequelae. There is paucity of large population studies evaluating childhood health care outcomes, including endocrine-related outcomes, in recent birth cohorts. Objectives To evaluate the rates of endocrine conditions during the first 5 years of life in children born preterm and term. Design/Methods The study cohort included liveborn infants at 22-44 weeks’ GA in British Columbia, Canada between 2004-2014. Follow-up data to December 2019 included linked health services use information from four BC provincial databases (perinatal database, hospitalizations, outpatient services, and outpatient prescriptions). Rates of outcomes were compared by GA at birth (37-44 weeks reference category) using robust Poisson regression. Results There were 455,960 children included in this study with 42,820 (9.4%) born at &amp;lt;37 weeks GA. Results are summarized in Table 1 and Table 2. Compared to children born at 37-44 weeks’ gestations, infants born at 36 weeks’ gestation or younger have an increased rate of thyroid disorders between 0 months and 5 years (rate ratio [RR]: 1.45, 95% confidence interval [CI]: 0.78-2.43; RR: 1.83, 95% CI 1.51-2.20; RR: 1.41 95% CI 1.26-1.57 for 22-27 weeks, 28-33 weeks and 34-36 weeks GA, respectively). Similarly, infants born at 36 weeks’ gestation or younger have a higher rate of conditions in growth and development (RR: 3.05, 95% CI: 0.76-7.96; RR: 3.20, 95% CI 2.04-4.76; RR: 1.42 95% CI 1.02-1.94 for 22-27 weeks, 28-33 weeks and 34-36 weeks gestations, respectively) and bone health conditions (RR: 1.38, 95% CI: 1.27-1.49; RR: 1.04, 95% CI 1.00-1.08; RR: 1.05 95% CI 1.03-1.07 for 22-27 weeks, 28-33 weeks and 34-36 weeks gestations, respectively). There was no difference in rates of conditions related to glucose metabolism such as diabetes mellitus or hypoglycemia. Conclusion Children born preterm have increased rates of endocrine conditions by age 5. Disorders of thyroid, growth and development are increased in infants born preterm. Children born preterm have an increase rate of bone-related disorders, including those born late-preterm. These results provide useful prognostic information for follow-up care for preterm children and for healthcare resource planning. Furthermore, these results highlight areas of future research in endocrine health among preterm infants.

Tremor after solid organ transplantation: Results from the TransplantLines Biobank and Cohort Study.

Tremor is a frequent complaint of solid organ transplant recipients. We report on the largest population investigated with clinical neurophysiological methods. Our aim is to objectively establish the tremor prevalence and syndrome in the largest population of solid organ transplant recipients. Tremor was measured in heart, kidney, liver, and lung recipients, using accelerometers during rest, postural, and weight-loaded conditions. The 95th percentile of healthy kidney donors' tremor amplitude was used as the cutoff to determine the presence of tremor in transplant recipients. Tremor frequency, frequency variability, and effect of loading were used to investigate enhanced physiological tremor as the likely tremor syndrome. Impact on activities of daily life was assessed, and correlations with tacrolimus blood levels were investigated. Tremor was present in 52% of 246 transplant recipients, typically in postural positions. Mean tremor frequency was 6.1 (±2.0) Hz; mean tremor variability was 2.6 (±1.8) Hz. A frequency decrease upon loading was found in 83% of patients with tremor. Sixty-five percent of patients met formal clinical neurophysiological criteria for enhanced physiological tremor. Tremor-related impairment was present in 55% and correlated with tremor amplitude (ρ = 0.23, p ≤ 0.001). In a binominal regression analysis, tacrolimus blood levels were independently associated with tremor prevalence (p = 0.009). More than half of solid organ transplant recipients experience a tremor that best fits the syndrome of enhanced physiological tremor. This is the first objective study on tremor that has established a better understanding of the neurophysiological mechanisms of tremor in a large population of solid organ transplant recipients.

Shifts in geographic vulnerability of US corn crops under different climate change scenarios: corn flea beetle (Chaetocnema pulicaria) and Stewart’s Wilt (Pantoea stewartii) bacterium

Abstract Changing climate patterns will likely affect insect pressure on many agricultural crops. Mild winters may decrease the number of insects that experience reduced fecundity or that are killed during hard freezes. This may result in larger populations in subsequent years and allow for range expansion. Direct effects from pests are compounded by indirect effects, such as crop damage resulting from insect-vectored diseases. Corn flea beetle (Chaetocnema pulicaria) infestations have both direct and indirect effects on crops. This beetle is a pest on all types of corn in the United States, including sweet corn and grain corn (sometimes referred to as dent corn). It is responsible for damage to plant foliage and also serves as the primary overwintering vector for Pantoea stewartii bacterium, which causes Stewart’s Wilt, a disease that can severely impact the health and productivity of corn. Evidence suggests that warmer winters will contribute to a geographic range expansion for the corn flea beetle. Here we show the projected northward expansion of economically damaging crop losses caused by Stewart’s Wilt: (A) from 1980 to 2011, (B) projected by mid-century, and (C) projected by end-century. Our work suggests that climate change and associated increasing winter temperatures in the United States will lead to a dramatic increase in the probability of severe damage from corn flea beetle across the United States, including the Corn Belt. Predicted increases in pest and disease pressure will have negative ramifications for corn production and are likely to exacerbate issues associated with specific management tactics, such as pesticide application.

Visual coding along multiple brain areas

This study focuses on understanding visual coding in multiple brain areas and its implications for neural processing in the visual system. It highlights the use of simultaneous recordings of large neuronal populations to investigate how visual information is encoded and processed in the brain. By studying the activity of multiple brain areas, the paper aims to uncover the mechanisms underlying brain-wide visual perception and provide insights into the neural basis of visual processing. The findings of this research contribute to the broader field of neuroscience and have implications for understanding visual disorders and developing therapeutic interventions