Factor Analysis Of Mixed Data Research Articles

Identifying Giant Cell Arteritis patients with higher risk of relapse and vascular events: a cluster analysis.

Giant cell arteritis (GCA) is one of the most common large vessel (LVV) vasculitis and is associated with a high risk of relapse and cardiovascular complications. Improving risk stratification remains a significant issue in this patient population. We aimed to perform a cluster analysis among GCA to identify clusters and evaluate their prognostic value. In a multicenter cohort study, we performed hierarchical cluster analysis on the factor analysis of mixed data coordinates results with 283 GCA patients' characteristics to generate clusters and assess incidence of relapse, cardiovascular events and death. Three clusters were identified: "Vascular relapsing profile" (23.0%), "Typical GCA profile" (47.7%), and "Ophthalmologic elderly profile" (29.3%). The "Vascular relapsing profile" cluster included younger patients with more frequent relapses and cardiovascular events, particularly thoracic aortic aneurysms. The "Typical GCA profile" was the largest, with classic cranial manifestations and frequently associated polymyalgia rheumatica. The "Ophthalmologic elderly profile" had the oldest patients with more visual loss and the highest mortality rate. Our findings underline the varied prognostic landscape within GCA, emphasizing the poor cardiovascular prognosis of younger patients with LV involvement and the higher mortality among elderly patients. This reinforces the need for further research regarding the screening of aortic abnormalities and whether those patients might benefit from intensive treatment with biotherapy and cardiovascular risk factors management.

Typology analysis of cattle farms in Northeast Algeria: Potential for sustainable development

CONTEXTCurrently, local cattle breeds are facing numerous challenges, and their disappearance could have social, economic, and environmental consequences. OBJECTIVEThis study was conducted in the northeast of Algeria to understand the characteristics, constraints of production systems and examine the specific strategies implemented in farms to ensure their viability. METHODA total of 175 smallholder farmers who practice Algerian local cattle breeding were interviewed using a structured questionnaire. Typology construction was carried out through factor analysis of mixed data, followed by sequential agglomerative hierarchical and K-means clustering, to define distinct farmer types with common characteristics. RESULTS AND CONCLUSIONResults highlight three farm types. The first group, representing 54.9% (96/175Farms) of the farms studied, is characterized by low-resource breeders who raise small herds of local breeds in association with small ruminants. Type 2 (25.7%) (45/175) consists of crossbred, diversified, supported breeding with better technical performance. The intensification strategies adopted by breeders of this type have relegated local cattle to the background. The third type (19.4%) (34/175) includes cattle pastoral farms, with the predominance of the local cattle breed characterized by limited productivity. SIGNIFICANCEThis study highlights farm diversity, the necessity of government support, and specific policies to ensure the sustainability of local cattle breeding, with particular emphasis on pastoral breeding, which has the largest number of local cattle breeds.

283 Identification of new or existing risk factors associated with the development of sow pelvic organ prolapse

Abstract A survey was conducted between March and December of 2022 to examine the variation between farms that had high and low pelvic organ prolapse (POP) rate. The objective was to identify new or existing risk factors associated with the development of POP, which could open new avenues for further investigation. Sow farms (n = 53) across 26 production systems located in the US, Canada, and Mexico were used. Sampling of farms was not random. High and low POP systems were selected within each region as well as high and low POP farms within each system. Over 800 variables related to general farm information and management, performance traits, reproductive management, replacement gilt management, gestation and farrowing practices, labor and health management, and nutrition were collected during farm visits. To be included in the analysis, at least 70% of observations were needed for continuous variables with at least 10% of observation for each category for categorical variables. Univariable models were fitted to identify variables associated with annualized POP rate for 2021. Variables with P ≤ 0.10 were selected for further analysis, with 94 predictor variables selected for principal components analysis (PCA). A factor analysis of mixed data was conducted, and results were then fitted into a hierarchical clustering on PCA, which segregated the data into three clusters: 2 with low POP (2.5%) and 1 with high POP (6.1%) prevalence (low vs high P < 0.05). The resulting clusters explained 33.7% of the variability in annualized 2021 POP rate. Differences between clusters were evaluated by Kruskall-Wallis test for numerical variables and chi-square test for categorical variables. High POP cluster farms had greater total piglets born over the years, greater number of sows per worker, greater annual gestation feed usage, and a lower mean body condition score at 16 wk of gestation compared with low POP cluster farms. High POP cluster farms had a decreased proportion of farms using conventional artificial insemination, a greater proportion of farms utilizing cup waterers in gestation for sows in group housing and in farrowing, and greater proportion of farms with a routine sleeving practice. High POP cluster farms compared with low POP cluster farms had greater gestation distillers dried grains with solubles (DDGS) inclusion level (14.6% vs 4.0%, SE 3.02), greater levels of standardized total tract digestibility (STTD) P% (0.49% vs 0.39%, SE 0.014), narrower analyzed Ca to STTD P ratio (1.7 vs 2.2, SE 0.06), and lower phytase inclusion and release (0.16% vs 0.09%, SE 0.014). These variables were also the predictors with the greatest R2 values in the univariable models. These observations suggest further research is needed to evaluate the connection between dietary Ca and P and pelvic organ prolapse.

Concept for enhanced intuition in development management through exploratory data analysis using an extended factor analysis of mixed data

AbstractWith the shift from mechanical value delivery to mechatronic value delivery, development environments are becoming more complex. Intuitive decision-making in development management is becoming increasingly challenging. Meanwhile, the use project management software is spreading, bringing about a new level of project data for development projects, holding to potential to enhance human decision making. To this end, the paper presents an extension to factor analysis of mixed data, which can facilitate usage of exploratory data analysis to improve decision-making in development project planning.

Patient Outcomes After Peripheral Nerve Injury Depend on Bimanual Dexterity and Preserved Use of the Affected Hand

Background Little is known about how peripheral nerve injury affects human performance, behavior, and life. Hand use choices are important for rehabilitation after unilateral impairment, but rarely measured, and are not changed by the normal course of rehabilitation and daily life. Objective To identify the relationship between hand use (L/R choices), motor performance, and patient-centered outcomes. Methods Participants (n = 48) with unilateral peripheral nerve injury were assessed for hand use via Block Building Task, Motor Activity Log, and Edinburgh Handedness Inventory; dexterity (separately for each hand) via Nine-Hole Peg Test, Jebsen Taylor Hand Function Test, and a precision drawing task; patient-centered outcomes via surveys of disability, activity participation, and health-related quality of life; and injury-related factors including injury cause and affected nerve. Factor Analysis of Mixed Data was used to explore relationships between these variables. The data were analyzed under 2 approaches: comparing dominant hand (DH) versus non-dominant hand (NH), or affected versus unaffected hand. Results The data were best explained by 5 dimensions. Good patient outcomes were associated with NH performance, DH performance (separately and secondarily to NH performance), and preserved function and use of the affected hand; whereas poor patient outcomes were associated with preserved but unused function of the affected hand. Conclusion After unilateral peripheral nerve injury, hand function, hand usage, and patient life arise from a complex interaction of many factors. To optimize rehabilitation after unilateral impairment, new rehabilitation methods are needed to promote performance and use with the NH, as well as the injured hand.

Clinical impact of proton pump inhibitors and other co-medications on advanced melanoma patients treated with BRAF/MEK inhibitors

PurposeWhile several studies reported the influence of co-medications on immune checkpoint therapy and chemotherapy, it remains poorly studied with targeted therapy. Targeted therapies inhibiting BRAF and MEK had significantly improved management of advanced melanoma with BRAFV600 mutation over the last decade, we aimed to investigate the possible influence of co-mediations on the efficacy and toxicity of these targeted therapies (TT). MethodsWe conducted an observational study identifying patients with advanced melanoma treated with BRAF/MEK inhibitors between 2013 and 2020 in the Bordeaux University Hospital. Co-medications given within 1 month before until 3 months after the initiation of targeted therapy were recorded and classified by their mechanism or by their metabolism. Survival data were analyzed with univariable and multivariable cox regression and the combined effect of multiple factors was evaluated using a factor analysis of mixed data (FAMD). The impact of co-medications on toxicity related to TT was also assessed. ResultsA total of 192 patients were included. Although several co-medications were associated with significantly shorter overall survival (OS) and/or progression-free survival (PFS), PPIs was the only co-medication with a significant impact in multivariable analysis considering all co-medications and specific prognostic factors. Co-medications did not influence the risk, type, or timing of TT-related toxicity. Additional FAMD revealed the impact of each factor on the oncological outcomes. In a subgroup of patients, residual plasma TT concentration was available and did not differ between PPIs users and non-users. ConclusionCo-medications, especially PPIs, must be carefully assessed at the time of TT initiation.

Evaluation and Modeling of Factors Associated with Drug Testing Appointment Absences

Abstract Introduction/Objective Why doesn't a patient show up for their appointment? Is it associated with the required travel distance? Urine drug testing clinics often observe patients' scheduled visit absenteeism and record the behavior on their profiles; these records were used to answer the question and explore other potential explanations. Methods/Case Report With a well-developed electronic health data system, a retrospective study was performed on a large data set collected across the US with more than half a million patient encounters to verify if our theories matched the statistical results. In addition, since the dataset was collected between January 2019 and December 2021, it has nearly a year of quarantine; thus, pandemic status was also analyzed as one variable. Patient demographic information (gender, race, and age), claimed drug use, participating programs, scheduling method, assigned risk of relapse, and collection site were included in the study too. Results (if a Case Study enter NA) For all required travel distance ranges, 40% of patients had unexplained absence on the record, and the frequency of missed appointments increased significantly (p < 0.001) by geographic distance from a clinic, including long distance (>20 miles) and walking distance (between 0-2 miles). Automated scheduling methods also demonstrated higher rates of missed appointments than manually scheduled visits. All demographic differences provide significant (p <= 0.001) but minimal effects on missed appointments. The overall rate of missing test appointments during the pandemic was higher and returned to pre-pandemic levels in 2021. Factor analysis of mixed data was used to give a clean and easy interpretation of the data set. Conclusion The required travel distance had an interesting impact on patient absenteeism rate; it increases the rate for both long and short walking distances. This study provides an empirical basis for healthcare providers to personalize service plans when scheduling patients’ visits.

Open population approach to identify risk factors and detection of cases of heart failure in Mexico

Abstract Heart failure (HF) is one of the cardiovascular diseases that in recent years has been a cause of high morbidity and mortality, worldwide it is estimated that 2% of the population lives with this heart condition. However, Mexico, despite having a high incidence of diseases associated with the development of HF, there are no clinical-epidemiological studies of the pathology. The present project is an epidemiological study on HF carried out by the civil association with the aim of identifying risk factors (RF) associated with the clinic that allow early diagnosis as well as transmitting guidelines that can prevent the development of the disease and/or its complications in the open population (OP) of Mexico. Cardiological assessments were conducted in some states of Mexico as a pilot test of the model designed by SL called Latidos Fest (LF). Each site had the following activities like vital signs, cardiac assessment, electrocardiogram and if indicated, echocardiogram. Those who attended the assessment had to sign an informed consent form and at the end received a summary with indications according to the clinical-epidemiological findings. With the data obtained, an Excel database was created in which descriptive analyses were also performed. The statistical model Factor Analysis of Mixed Data (FAMD) was generated to identify quantitative and qualitative variables associated with the presence of HF and a classification tree model to establish the hierarchical value of the variables and their predictive value for the risk and detection of HF cases. For both statistical models RStudio software was used. A total of 949 cardiac evaluations in OP were performed thanks to the NGO of the LF in 7 different states of Mexico during 2022. In 68.1% of the population, at least 1 RF for developing HF was detected, 16.33% were identified as having HF with no previous diagnosis (PD), 0.74% already had a PD and 14.12% were apparently healthy. The demographic variables with the highest percentage are shown in table 1. From the FAMD model, the variables in which the individuals coincided most are shown in figure 1-A. When performing the classification trees, the overall prediction associated (OPA) to cases with and without HF was 75% confidence of which, the accuracy of classifying a case with HF was 67.4% and without HF was 82.2%; for the OPA for the risk of developing HF and not having HF the confidence was 82%, in this the accuracy of classifying without HF was 15%, however, the accuracy of classifying someone at risk of developing HF was 95.8% (Figure 1-B). Thanks to the cardiology assessments in OP that were performed in each LF, risk factors and new cases of HF were identified. With the findings in the models, it is possible to intentionally search for people with the factors found, however, it is necessary to expand the cardiological screening in other populations to check if the clinical-epidemiological parameters match or are different.Table 1.Percentage of demographic variaFigure 1.Results of the models. A. FAMD

T2D triggers distinct cardiac transcriptomic signatures in patients with severe aortic stenosis

Abstract Type 2 diabetes (T2D) is often associated to left ventricular (LV) pressure overload, as in aortic stenosis (AS). We reported, on DIAPASON cohort, that T2D increases adverse cardiac remodelling and dysfunction in patients with severe AS referred for aortic valve replacement. We aimed to study the underlying molecular mechanisms by a transcriptomic approach. We realised a transcriptomic analysis of LV cardiac biopsies obtained during aortic valve surgery from 17 T2D and 30 non-diabetic patients. Principal component analysis (PCA), on the 1029 significantly differentially expressed genes, shows a general segregation between T2D and non-diabetic patients. Functional enrichment maps reveal that 4 major biological processes are upregulated in T2D patients: regulation of inflammation, adaptation to cardiac hypertrophy, regulation of endothelial function/angiogenesis, and organisation of extracellular matrix. Decreased gene expression by T2D gathers 4 major biological processes: regulation of cardiac muscle contraction, mitochondrial organization, organization of mitochondrial respiratory chain and amino acid metabolism. After adjustment with other T2D comorbidities (age, sex, hypertension, BMI or the 4 combined), T2D effect remains mainly significant on the upregulated biological processes whereas the downregulation of amino acid metabolism, regulation of cardiac muscle contraction and mitochondrial transport processes seems to depend on hypertension and age. As an overlap was still present between T2D and non-diabetics transcriptomes in the PCA, we decided to use Factor Analysis of Mixed Data to identify potential subgroups of patients among the whole cohort. 84 patients have been clustered into 3 groups. Cluster 1 is associated with a patient profile without T2D and displaying a mild cardiac dysfunction, contrary to cluster 3 which includes mainly male T2D patients with a pronounced structural and functional cardiac alteration. Cluster 2 is only composed of female patients with higher BMI and leptin serum level, diastolic alteration and a moderately increased hypertrophy. Biological processes were differently affected between cluster 1 and cluster 2 or 3. Cluster 2 presents a decrease in gene expression involved in histone and protein demethylation. As for cluster 3, the expression of genes involved in immune response processes is increased while the one for the regulation of cardiac muscle organisation is decreased. To conclude, T2D is specifically associated with a reduction of gene expression involved in mitochondrial function, and an upregulation of angiogenesis, inflammation, and organisation of extracellular matrix. The unsupervised analysis revealed different clusters with specific gene expression and more specifically an association of female sex and metabolic syndrome with demethylation processes, and an association of T2D in men with inflammation and dysregulation of cardiac muscle contraction processes.Biological process in T2D patients

Effect of Gap Size and Elevation on the Regeneration and Coexistence of Abies, Betula, and Acer Tree Species in a Subalpine Coniferous Forest

Forest gaps play an important role in species regeneration and forest succession. Gap size has a primary influence on tree species coexistence and community assembly along an elevation gradient. In this study, we evaluated the regeneration and coexistence of Abies faxoniana, Betula utilis, and Acer maximowiczii at different life history stages in varied gap sizes along an elevation gradient (between 3000 and 3500 m a.s.l). We found that gap size can positively enlarge the effects of elevation on the regeneration density of the three species. In the process of regeneration from seedling to sapling, Abies had stronger regeneration capability, with regeneration niche breadths of more than 0.6 in different gap sizes. A factor analysis of mixed data indicated that regeneration density, soil nutrient contents, and air humidity were mainly related to gap size, but habitat temperature was largely determined by elevation. The connection between the species regeneration density and habitat conditions was due to differences in their regeneration niches, reflecting the selective preemption of environmental resources of different species in different life stages. Microhabitat heterogeneity, controlled by the characteristics of forest gaps along an elevation, affected the regeneration niche differences of the tree species, which contributed to the species coexistence and community assembly processes.

Gestational toxoplasmosis treatment changes the child's prognosis: A cohort study in southern Brazil.

We evaluate the drug treatment for pregnant women with acute toxoplasmosis to reduce the risk of congenital infection, side effects (prenatal and postnatal treatment in children) and the hazard of discontinuing the infant's medication. We conducted a prospective cohort study to assess the risks of congenital toxoplasmosis among children born to acutely infected women with and without treatment. We examined the relationship between "exposed" and "infected children", "number of infant neutrophils", "prenatal" and "postnatal treatment". Factor analysis of mixed data (FAMD) was used to analyze the data. All children started treatment at the hospital. Between 2017 and 2021, 233 pregnant women were evaluated at the University Hospital of Maringá; ninety-four met criteria for acute gestational toxoplasmosis. We followed up 61 children; eleven (18%) had the infection confirmed and 50 (82%) were free of toxoplasmosis (exposed). Children born to untreated mothers have 6.5-times higher risk of being infected; the transmission rate among untreated mothers was 50% versus 8.3% among treated ones. Three decreasing values of immunoglobulin G were a security parameter for stopping the child's medication in the exposed group (50/61). Neutropenia was the leading side effect among children and the infected had a 2.7 times higher risk. There was no correlation between maternal use of pyrimethamine and children's neutropenia. The follow-up of women with acute T. gondii infection and their children, through a multidisciplinary team, availability of anti-T. gondii serology and pre- and post-natal treatments reduced the risk of toxoplasmosis transmission.

The effectiveness of supervised clustering for characterising flight diversions due to weather

Flight diversions due to adverse weather have a significant negative impact on airspace users, airports, and the environment. Previous work proposed a tree-based model that learned which flights are more likely to be diverted due to adverse weather conditions at the destination airport from historical traffic and weather data. This model was trained using confident learning to exclude from training unpredictable flight diversions caused by reasons other than weather, such as medical emergencies or technical problems. Aggregated performance metrics computed on the test set demonstrated high precision and moderate recall, and inspection of the Shapley values unravelled the most important features. Initial human observations made during the live trial, however, have raised a potential connection between the quality of predictions and the specific weather conditions that lead to flight diversions. This study aims to provide empirical evidence to support this hypothesis. To accomplish this, a data-driven methodology should be used to characterise the main conditions that cause flight diversions. Concurrently, the effectiveness of the model in each of these conditions should be evaluated. The dataset under consideration, however, presents a challenge because it contains a plethora of high-cardinality categorical features (e.g., destination airport and aircraft operator) as well as skewed numerical features with a wide range of scales (e.g., visibility and wind gust). This scenario significantly increases the difficulty of characterising the main conditions that cause flight diversions and conducting subsequent analyses even with established methods like factor analysis of mixed data. To address this challenge, this paper proposes to utilise supervised clustering, a method that combines state-of-the-art feature attribution, dimensionality reduction, and clustering algorithms to identify the most representative decisions of a model. Following that, the distinctive characteristics of the various decisions (e.g., extreme obscuration at the airport), each associated with a cluster, are determined by examining them. Finally, conventional classification and uncertainty metrics are computed for each cluster to assess the performance of the model. This paper shows that supervised clustering is effective in characterising flight diversions due to weather, and provides valuable insights into the performance of the model in different conditions, highlighting situations where predictions require careful consideration.

Development and validation of a clinical model for predicting the severity of carpal tunnel syndrome.

Pain, discomfort, and cost may result in incomplete or inconclusive electrodiagnostic studies to assess the severity of carpal tunnel syndrome. We aimed to develop a clinical instrument for stratifying patients based on easy-to-measure variables to assess carpal tunnel syndrome severity. We performed a secondary analysis of data from patients diagnosed with a diagnosis of carpal tunnel syndrome using a factor analysis of mixed data. In total, 1037 patients (405; 39.1% male) with a mean (SD) age of 58.0 (10.8) years were included. For each patient, demographic information, physical examination findings, ultrasonographic findings, and the severity of the syndrome based on electrodiagnostic studies were recorded. We devised a composite index incorporating a pain numeric rating scale (NRS) rated from 0 (no pain at all) to 10 (the worst pain ever possible), presence of thenar muscle weakness or atrophy (TW), cross-sectional area (CSA) of the median nerve (mm2), and occurrence of nocturnal pain (NP). The composite index was calculated as [scale(NRS)+scale(CSA)+NP+TW]/4, where both NP and TW are binary features (0 or 1). The overall accuracy and area under the curve of the index for stratifying the syndrome severity were 0.85 and 0.71, respectively (Cohen's Kappa = 0.51, McNemar's test P = 0.249). The composite index increased pretest probability by 1.6, 1.8, and 3.3 times with positive likelihood ratios of 3.3, 2.5, and 13.5, and false-positive rates of 26.6, 17.6, and 4.8% for mild, moderate, and severe syndrome, respectively. The index thresholds for mild, moderate, and severe carpal tunnel syndrome were <0.8, ≥0.8 to <1.1, and ≥1.1, respectively. Using a composite index, patients with carpal tunnel syndrome can be categorized for the severity of the syndrome before carrying out electrodiagnostic studies.

Inheriting the sins of their fathers: boar life experiences can shape the emotional responses of their offspring

IntroductionThe welfare of breeding boars is often overlooked, resulting in limited scientific data to foster discussion of the topic. We aimed to investigate the effect of different boar housing conditions on their offspring’s emotionality.MethodsEighteen boars were housed in three different conditions: crates (C; n = 6), pens (P; n = 6), or enriched pens (E; n = 6). Boars were distributed by semen quality (SQ; high, medium, or low). Three semen pools were used to inseminate 13 gilts housed in outdoor paddocks. At 25 days of age, 138 suckling piglets were subjected to open field (OF), novel object (NO), and elevated plus-maze (EPM) tests. Saliva was collected before and after the OF and NO tests to measure cortisol concentrations. At the end of the experiment, hair samples were collected for DNA paternity tests. Piglets were classified based on their behavioral responses using hierarchical cluster analysis of the principal components extracted from factor analysis of mixed data. The variables were reduced to seven principal components (dimensions, Dims), which explained 73% of the total variation, and were analyzed using linear mixed models. The models included each Dim as a dependent variable, paternal treatment and body weight (BW) as fixed effects, and paternal SQ as a random effect. Kruskal−Wallis and Wilcoxon rank-sum tests were used to compare the cortisol concentration ratios (before and after the OF and NO tests) between groups.ResultsThere was an effect of treatment on Dim 3 (EPM; activity/fear), with higher values in C piglets than E piglets (p = 0.047). Although C piglets had significantly higher values than P piglets in Dim 4 (EPM; anxiety; p = 0.029) and Dim 6 (NO; inactivity far from the object/exploration; p &amp;lt; 0.0001), the effect of the paternal treatment × BW interaction was significant in both dimensions (p &amp;lt; 0.05). The cortisol ratio in E piglets was greater than that in P and C piglets (p &amp;lt; 0.05).Discussion and conclusionOur findings indicate that boar breeding environments affect the stress response and emotionality (anxiety, fear, and exploration) of their offspring.

Differences in perceived threat and trauma in children during the COVID-19 pandemic

BackgroundThe past 2 years of the COVID-19 pandemic were stressful for most children and adolescents; some children may have experienced a high level of stress and trauma. To date, no study has examined self-reported stress and trauma levels due to COVID-19 in children. This study aimed to assess perceived threat, exposure and trauma symptoms in children aged 7–13 years. In addition, we explored whether parent-reported factors could predict a higher risk of COVID-19 vulnerability in their children.MethodCross-sectional data were collected from 752 children to assess COVID-19 threat, exposure and trauma symptoms using the self- and parent-reported Child and Adolescent Trauma Screening Self-Report (CATS) Trauma questionnaire. We used exploratory analyses (factor analysis of mixed data and hierarchical clustering) to identify subgroups (i.e., clusters) of children sharing similar characteristics in the dataset. Linear regression modeling was applied to determine the likelihood of higher threat and vulnerability in children with parent-reported COVID-19 threat, exposure, CATS trauma symptoms, behaviors on the Child Behavior Checklist (CBCL), and posttraumatic growth (PTG).ResultsWe identified a high-risk group of children reporting clinically relevant trauma symptoms and COVID-19-related fears. Parents’ reports of trauma could be used to identify children at high risk.ConclusionsApproximately 25% of children reported moderate to clinically relevant levels of trauma symptom. It is especially important to offer adequate support to these children to ease the trauma and prevent their symptoms from developing into psychopathology.

Typology of Dementia-Specific Care Units: A Nationwide Survey Study in Germany.

Dementia-specific care units vary in their organizational characteristics and are difficult to compare in empirical studies. Based on a representative sample of care units in German nursing homes, we present a typology of organizational characteristics focusing on dementia-specific care structures. We also examine the relationships between organizational types and the provision of nonpharmacological interventions for people with dementia. Data were collected in a Germany-wide survey of a stratified randomized sample of 134 care units using a standardized questionnaire administered during telephone interviews with nursing home administrators or their representatives. The typology was developed based on a factor analysis of mixed data and a hierarchical cluster analysis. We identified 4 types of care units: Dementia Care Units (DCUs; n = 40), Dementia Special Care Units (DSCUs; n = 17), Usual Separated Care Units (n = 58), and Usual Incorporated Care Units (n = 19). All care unit types clearly differed in their organizational characteristics. The specialization of DSCUs was agreed upon with cost bearers and included admission criteria, higher costs, and better staff conditions. Dementia Care Units without specialization did not have these characteristics. Three of seven nonpharmacological interventions were associated with the DSCUs and two with DCUs, but not with the other care unit types. Researchers can use the typology to define and describe care units in empirical studies and improve the understanding and comparability of the context. A clear definition of care units also improves international comparisons.

The Impact of COVID-19-Induced Responsibilities on Women’s Employment in Arab Countries

The COVID-19 pandemic has created massive challenges for women’s employment. Women’s responsibilities were exacerbated by the closure of schools and child daycare facilities. Investigating the determinants of job losses among women is critical to avoiding dropouts and supporting re-entry into the labor market. This study investigates the factors driving women’s workforce losses during the pandemic in five Arab countries (Egypt, Tunisia, Morocco, Jordan, and Sudan). The current study focuses mainly on how COVID-19-induced responsibilities affected women’s employment during the pandemic. The study depends on the COVID-19 MENA Monitor Household Survey produced by the Economic Research Forum. The factor analysis of mixed data is used to construct the women’s responsibilities index that is made up of 18 variables. The mixed-effect logistic model is used to consider changes in working arrangements across economic activities. The results indicate that women with high family caregiving responsibilities were more likely to lose their jobs. Women working in the government sector and with health insurance were protected from job losses. Telecommuting played a significant role in helping women maintain their jobs. Work arrangements should be improved to consider increased unpaid domestic work. Family-friendly policies must be activated, and childcare leave must be facilitated and funded. The private sector should also be urged to improve workplace flexibility.

Spectral Features Differentiate Aging-Induced Changes in Parchment-A Combined Approach of UV/VIS, µ-ATR/FTIR and µ-Raman Spectroscopy with Multivariate Data Analysis.

From the moment of production, artworks are constantly exposed to changing environmental factors potentially inducing degradation. Therefore, detailed knowledge of natural degradation phenomena is essential for proper damage assessment and preservation. With special focus on written cultural heritage, we present a study on the degradation of sheep parchment employing accelerated aging with light (295-3000 nm) for one month, 30/50/80% relative humidity (RH) and 50 ppm sulfur dioxide with 30/50/80%RH for one week. UV/VIS spectroscopy detected changes in the sample surface appearance, showing browning after light-aging and increased brightness after SO2-aging. Band deconvolution of ATR/FTIR and Raman spectra and factor analysis of mixed data (FAMD) revealed characteristic changes of the main parchment components. Spectral features for degradation-induced structural changes of collagen and lipids turned out to be different for the employed aging parameters. All aging conditions induced denaturation (of different degrees) indicated by changes in the secondary structure of collagen. Light treatment resulted in the most pronounced changes for collagen fibrils in addition to backbone cleavage and side chain oxidations. Additional increased disorder for lipids was observed. Despite shorter exposure times, SO2-aging led to a weakening of protein structures induced by transitions of stabilizing disulfide bonds and side chain oxidations.

Multimodal Phenomap of Stargardt Disease Integrating Structural, Psychophysical, and Electrophysiologic Measures of Retinal Degeneration

To cluster the diverse phenotypic features of Stargardt disease (STGD) using unsupervised clustering of multimodal retinal structure and function data. Retrospective cross-sectional study. Eyes of subjects with STGD and fundus autofluorescence (FAF), OCT, electroretinography (ERG), and microperimetry (MP) data available within 1year of the baseline evaluation. A total of 46 variables from FAF, OCT, ERG, and MP results were recorded for subjects with STGD as defined per published criteria. Factor analysis of mixed data identified the most informative variables. Unsupervised hierarchical clustering and silhouette analysis identified the optimal number of clusters to classify multimodal phenotypes. Phenotypic clusters of STGD subjects and the corresponding cluster features. We included 52 subjects and 102 eyes with a mean visual acuity (VA) at the time of multimodal testing of 0.69±0.494 logarithm of minimum angle of resolution (20/63 Snellen). We identified 4 clusters of eyes. Compared to the other clusters, cluster 1 (n=16) included younger subjects, VA greater than that of clusters 2 and 3, normal or moderately low total macular volume (TMV), greater preservation of scotopic and photopic ERG responses and fixation stability, less atrophy, and fewer flecks. Cluster 2 (n=49) differed from cluster 1 mainly with less atrophy and relatively stable fixation. Cluster 3 (n=10) included older subjects than clusters 1 and 2 and showed the lowest VA, TMV, ERG responses, and fixation stability, with extensive atrophy. Cluster 4 (n=27) showed better VA, TMV similar to clusters 1 and 2, moderate ERG activity, stable fixation, and moderate-high atrophy and flecks. Reflecting the phenotypic complexity of STGD, an unsupervised clustering approach incorporating phenotypic measures can be used to categorize STGD eyes into distinct clusters. The clusters exhibit differences in structural and functional measures including quantity of flecks, extent of retinal atrophy, visual fixation accuracy, and ERG responses, among other features. If novel pharmacologic, gene, or cell therapy modalities become available in the future, the multimodal phenomap approach may be useful to individualize treatment decisions, and its utility in aiding prognostication requires further evaluation. Proprietary or commercial disclosure may be found after the references.

VARIABILITY ANALYSIS OF WILD GUATEMALAN AVOCADO GERMPLASM BASED ON AGRO-MORPHOLOGICAL TRAITS

&lt;p&gt;&lt;strong&gt;Background. &lt;/strong&gt;For the Guatemalan culture, the avocado (&lt;em&gt;Persea americana&lt;/em&gt; Mill) represents more than a crop, since it has religious, mythical, economical, and medicinal significance typical of the center of domestication of the species. Although there is speculation about the wide variability of wild avocado germplasm, there are no studies describing avocado populations. &lt;strong&gt;Objective.&lt;/strong&gt; To explore wild germplasm based on agro-morphological characteristics using the standardized descriptors for avocado (&lt;em&gt;Persea&lt;/em&gt; spp.). &lt;strong&gt;Methodology. &lt;/strong&gt;The distribution of characteristics of 189 avocado trees across eight populations was evaluated using cross-tabulation and Chi-square testing. In order to properly handle qualitative and quantitative data, it was employed the factor analysis of mixed data (FAMD) and hierarchical clustering on principal components (HCPC) to analyze the relationship and variation of features within and between populations. &lt;strong&gt;Results.&lt;/strong&gt; The samples showed various morphological characteristics that indicate the presence of Mexican, Guatemalan, and West Indian avocado races in Guatemala. The FAMD revealed that the fruit shape, skin color and flesh texture, and anise odor in the leaves are ideal traits for distinguishing between individual trees. At the population level, the HCPC showed considerable variance amongst the studied trees but no distinct geographic groups of the samples. &lt;strong&gt;Implications.&lt;/strong&gt; Although not all wild avocados grown in Guatemala are of the highest quality, several trees of extraordinary excellence are strewn over the republic's highlands. Thus, due to the danger posed by the introduction of commercial varieties, it is advisable preserving the germplasm. &lt;strong&gt;Conclusion. &lt;/strong&gt;The clustering methods revealed that the 189 avocado trees could be regrouped into three main clusters. The morphological descriptors proved to be useful for grouping trees according to known races and can therefore be used in the characterization of cultivars and wild trees whose ancestry is unknown.&lt;/p&gt;