Miracle-dz/UniFAR-FTUs huggingface dataset:
Urban landscape and infection risk in free‐roaming cats

Despite public concern on the role of free‐roaming cats as reservoirs of zoonotic agents, little is known about the influence of urban and peri‐urban landscapes on the exposure risk. We evaluated the seroprevalence of three zoonotic agents (Chlamydia felis, Coxiella burnetii and Toxoplasma gondii) in domestic cats (Felis catus). Two hundred and ninety‐one free‐roaming cats were trapped in Murcia municipality (Southeast Spain), and their sera were tested for specific antibodies against T. gondii using a modified agglutination test (MAT), and for C. felis, C. burnetii and feline immunodeficiency virus (FIV) antibodies with ELISA technique. Pathogen seroprevalence at 95% CI was calculated for each sex and age category (up to and over 12 months) and compared with a chi‐squared test. The role of human population density and urban landscape characteristics on the risk of pathogen exposure in the cat population was explored using generalized linear models. Seropositivity against a single pathogen was found in 60% of the cats, while 19% was seropositive for two or three pathogens. Seroprevalence of C. felis was 8% (CI95%: 5–11), 37% (CI95%: 31–42) for C. burnetii and 42% (CI95%: 36–47) for T. gondii. In addition to these three pathogens, FIV seropositivity was low (1%, CI95%: −0.1 to 2) and adult cats were more likely to be seropositive to C. burnetii than young individuals (OR: 2.3, CI95%: 1.2–4.2). No sex or age class differences in seroprevalence were observed for the rest of the pathogens. Seropositivity was correlated with water surface areas for C. felis, and not with crop areas. Coxiella burnetii seropositivity was correlated with the percentage of urban areas (continuous with only buildings and discontinuous, that include buildings, parks, and pedestrian and urban green areas), human population size and peri‐urban areas with shrubs, and not correlated with other agricultural landscapes (orchards and crop areas). However, the seroprevalence of T. gondii was only associated with agricultural landscapes such as orchards. The detection of hotspot areas of high pathogen exposure risk is the basis for municipal services to implement surveillance and risk factor control campaigns in specific‐risk areas, including (a) efficient health management of urban cat colonies by geographical location, population census and health status monitoring of the components of each cat colony, (b) improvement of hygiene and sanitary conditions at the feeding points of the cat colony and (c) free‐roaming cat trapping for health monitoring and, in the long term, to know the evolution of the health status of their populations.
The potential utility of smell testing to screen for neurodegenerative disorders

ABSTRACT Introduction Loss of smell is a common early feature of neurodegenerative diseases including Alzheimer’s and Parkinson’s disease. Identifying these conditions in their early stages is important to understand more about early pathophysiological events and the development of disease modifying therapies. Smell testing may be an effective future tool for screening large populations for early neurodegeneration. Areas Covered In this review, we appraise the evidence for, and discuss the likelihood of, the use of smell testing in large screening programs to detect early neurodegeneration. We evaluate the predictive power of smell tests for neurodegenerative disease, compare performance to other established screening programs, and discuss ethical and practical considerations and limitations. Expert Opinion Even if disease modifying therapies were available for neurodegenerative disease, smell tests alone are unlikely to have high enough predictive power to be used in a future screening program. However, we believe they could be a valuable component of a short battery of tests or part of a stepwise process that together could more accurately identify early neurodegeneration in large populations.
A Multi-Task Learning Framework for Automated Segmentation and Classification of Breast Tumors From Ultrasound Images

Breast cancer is one of the most fatal diseases leading to the death of several women across the world. But early diagnosis of breast cancer can help to reduce the mortality rate. So an efficient multi-task learning approach is proposed in this work for the automatic segmentation and classification of breast tumors from ultrasound images. The proposed learning approach consists of an encoder, decoder, and bridge blocks for segmentation and a dense branch for the classification of tumors. For efficient classification, multi-scale features from different levels of the network are used. Experimental results show that the proposed approach is able to enhance the accuracy and recall of segmentation by 1 . 08 % , 4 . 13 % , and classification by 1 . 16 % , 2 . 34 % , respectively than the methods available in the literature.
The Effect of Uncertainties on Multi-Echelon Serial Supply Chains

Uncertainties are the major concerns in supply chain because existence of uncertainties degrades the performance of supply chain. Hence, business executives need to seriously focus towards controlling the effect of uncertainty on supply chain performance. In this study, a four echelon serial supply chain employed with reorder-point order-up-to level inventory replenishment (s, S) policy is modeled using system dynamics approach. Manufacturing systems adopting make-to-stock (MTS) and assemble-to-stock (ATS) manufacturing policy and operating under uncertain environment are modelled through system dynamics approach. A serial two-stage MTS manufacturing system is modelled through system dynamics approach and the behaviour is studied under the influence of uncertainty in demand, lead time, supplier’s acquisition rate, processing time and delay due to machine failure. Two different improved demand forecasting models are proposed to enhance the forecasting accuracy and reduce the bullwhip effect (BWE) and net-stock amplification (NSAmp). The first proposed model is the integrated approach of autoregressive integrated moving average (ARIMA) and generalized autoregressive conditional heteroskedasticity (GARCH) model denoted as ARIMA-GARCH to overcome the problem related to heteroskedastic nature of demand series. Second proposed model is the integrated approach of discrete wavelet transformation (DWT) and intelligence technique such as artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS), least square support vector machine (LSSVM) and multi-gene genetic programming (MGGP) to deal with non-linear, non-stationary demand series. Simulation study of multi-echelon supply chain indicates that target inventory significantly influence the BWE and it can be reduced through keeping target inventory at low level when there is low uncertainty in demand and lead time. From the analysis of manufacturing supply chain, it is observed that backlog at manufacturer’s end is significantly influenced by uncertainty in processing time and delay due to machine failure. The backup strategy adopted in manufacturing supply chain reveals that performance of manufacturing system is highly affected when uncertainty in supplier’s acquisition rate increases. The study proves that maintaining high service level at the bottom echelon is required to achieve high service level at the upper echelon of a supply chain. From the forecasting study, it is found that performance of the ARIMA-GARCH model outperforms the ARIMA model. Further, it is proved through case-study examples
Incidence of Seizure and Associated Risk Factors in Patients in the Medical Intensive Care Unit (ICU) at Memorial Sloan Kettering Cancer Center (MSK) from 2016–2017

Background: Seizures and status epilepticus are common neurologic complications in the intensive care unit (ICU) but the incidence in a cancer ICU is unknown. It is important to understand seizure risk factors in cancer patients to properly diagnose the seizure type to ensure appropriate therapy. Methods: We identified patients admitted to the medical ICU at Memorial Sloan Kettering Cancer Center (MSK) from January 2016 to December 2017 who had continuous or routine electroencephalography (EEG) and identified clinical and electrographic seizures by chart review. Results: Of the 1059 patients admitted to the ICU between 2016 and 2017, 50 patients had clinical and/or electrographic seizures (incidence of 4.7%, 95% CI: 3.4-6.0). The incidences of clinical and electrographic seizure were 4.1% and 1.1%, respectively. In a multivariable stepwise regression model, history of seizure (OR: 2.9, 95% CI: 1.1-7.8, P: .03), brain metastasis (OR: 2.5, 95% CI: 1.1-5.8, P: .03), vasopressor requirement (OR: 2.2, 95% CI: 1.0-4.9, P: .05), and age < 65 (2.4, 95% CI: 1.2-5.0, P: .02) were associated with increased risk of seizure (either clinical or electrographic). Obtaining continuous EEG instead of routine EEG increased the yield of seizure detection significantly (OR: 3.9, 95% CI: 1.3-11.1, P: .01). No chemotherapy in the past 30 days, no antibiotic use, vasopressor requirement, and having a brain tumor increased risk of electrographic seizure. Length of continuous EEG > 24 h significantly increased the chances of both clinical and electrographic seizure detection, (OR: 2.6 [95% CI: 1.2-5.7] and 15.0 [95% CI: 2.7-82.5], respectively). Conclusions: We identified known and cancer-related risk factors which can aid clinicians in diagnosing seizures in cancer ICUs. Long-term video EEG monitoring should be considered, particularly given the treatable and reversible nature of seizures.
16S rDNA sequencing analyzes differences in intestinal flora of human immunodeficiency virus (HIV) patients and association with immune activation

ABSTRACT To clarify the influence of HIV on the intestinal flora and the interrelationship with CD4 T cells, the present study collected stool specimens from 33 HIV patients and 28 healthy subjects to compare the differences in the intestinal flora and CD4 T cells in a 16S rDNA-sequencing approach. ELISA was used to detect the expressions of interleukin 2 (IL-2), IL-8, and tumor necrosis factor-α (TNF-α). Meanwhile, correlation analysis with the different bacterial populations in each group was carried out. The results revealed that Alpha diversity indices of the intestinal flora of HIV patients were markedly lower than that of the healthy group (p < 0.05). The top five bacterial species in the HIV group were Bacteroides (23.453%), Prevotella (19.237%), Fusobacterium (12.408%), Lachnospira (3.811%), and Escherichia-Shigella (3.126%). Spearman correlation analysis results indicated that Fusobacterium_mortiferum, Fusobacterium, and Gammaproteobacteria were positively correlated with TNF-α (p < 0.05), whereas Ruminococcaceae, Bacteroidales was negatively correlated with TNF-α (p < 0.05). Additionally, Agathobacter was positively correlated with contents of IL-2 and IL-8 (p < 0.05), whereas Prevotellaceae, and Prevotella were negatively correlated with IL-8 content (p < 0.05). Furthermore, the top five strains in the CD4 high group (≥350/mm3) included Bacteroides (23.286%), Prevotella (21.943%), Fusobacterium (10.479%), Lachnospira (4.465%), and un_f_Lachnospiraceae (2.786%). Taken together, the present study identified that Fusobacterium and Escherichia-Shigella were specific and highly abundant in the HIV group and a correlation between the different bacterial flora and the contents of IL-2, IL-8, and TNF-α was revealed.
Implementation of an internet-based asthma patient education program in primary care: results of a single-arm trial

Abstract Objective: Asthma education programs (AEPs) for patients are known to be important to provide skills to effectively manage the disease. We developed an electronic AEP (eAEP) and assessed the extent to which patients with asthma in primary care are capable to use the eAEP and whether asthma knowledge improved after eAEP. Methods: A single-arm pilot study was performed between November 2019 and December 2020 in 12 general practices in Upper Bavaria, Germany. Asthma knowledge was assessed by the Asthma Knowledge Test (AKT) at baseline, 2 weeks after completion of the eAEP, as well as after 3 and 6 months. AKT sum scores at baseline and follow-up were compared with each other using the Wilcoxon test. Results: In total, 72 patients with asthma were included, of whom all participated in the 2-week follow-up, while data on the 3- and 6-month follow-up was available in 62 and 51 patients, respectively. The eAEP was well accepted and positively evaluated by participants. The mean AKT score significantly (p < .001) increased from 22.8 ± 11.0 at baseline to 44.6 ± 8.3 two weeks after completion of the eAEP. After 3 months, the mean score was still 41.8 ± 7.6, and after 6 months it was 40.2 ± 9.3 (p < .001 each compared to baseline). Conclusions: The internet-based asthma education program was well accepted by primary care patients and resulted in a major increase of asthma knowledge. Thus, it has the potential to be an important adjunct in the treatment of patients with asthma in general practice.
Dual DNA staining enables isolation of multiple sub‐types of post‐replicative mouse male germ cells

During spermatogenesis, mammalian male germ cells undergo multiple developmental processes, including meiosis and post‐meiotic differentiation (spermiogenesis). To understand the transitions between different cellular states it is essential to isolate pure populations of cells at different stages of development. Previous approaches enabled the isolation of cells from different stages of meiotic prophase I, but techniques to sub‐fractionate unfixed, post‐meiotic spermatids have been lacking. Here we report the development of a protocol enabling simultaneous isolation of cells at different stages of meiotic prophase and post‐meiotic differentiation from testes of adult mice. This approach builds on existing fluorescence activated cell sorting protocols designed to purify cells in different stages of meiotic prophase I. By utilizing the specific spectral properties that two different DNA dyes (Hoechst 33342 and SYTO 16) exhibit when bound to chromatin of different stage male germ cells, we obtain highly pure populations of cells in relatively large numbers. This FACS protocol will enable immunocytological and molecular characterization studies of fractionated meiotic and haploid germ cells from both wild type and genetically mutant animals.
Decreasing colorectal cancer screening disparities: A culturally tailored patient navigation program for Hispanic patients

Colorectal cancer (CRC) is the second leading cause of cancer‐related death in Hispanic patients. Screening colonoscopy has been shown to reduce the incidence and mortality of CRC. However, utilization among Hispanic patients and other minority groups is low. The objective of this study was to evaluate colonoscopy utilization among Hispanic patients with a culturally tailored patient navigation program (CTPNP) in place.
Type 1 diabetes, cognitive ability and incidence of cardiovascular disease and death over 60 years of follow‐up time in men

There are few cohorts of type 1 diabetes that follow individuals over more than half a century in terms of health outcomes. The aim of this study was to examine associations between type 1 diabetes, diagnosed before age 18, and long‐term morbidity and mortality, and to investigate whether cognitive ability plays a role in long‐term morbidity and mortality risk.
Using an external focus of attention for gait retraining in runners: A case report

ABSTRACT Introduction Many gait retraining studies use cues that promote internal focus of attention. However, the motor control literature clearly shows the beneficial effects of using cues that promote an external focus of attention (EFOA) when teaching new movements. This case report seeks to illustrate the outcomes of using an EFOA for running gait retraining. It also examines whether retrained mechanics transfer across different running speeds. Case Descriptions A 22-year-old female competitive runner with a history of tibial stress injuries was the participant. Patient Management Baseline assessments of flexibility, strength, and running biomechanics were performed after which an eight-session gait retraining protocol was implemented. Visual (mirror) and verbal feedback (EFOA) cues were provided during the retraining protocol. Outcomes showed improved hip, knee, and ankle kinematics, reduced ground reaction forces, and earlier onset and longer durations of muscle activity following retraining. These improvements transferred across running speeds. Discussion and Conclusion In this participant, EFOA cues were effective for the gait retraining protocol and the benefits were transferable across running speeds. Clinicians should consider how EFOA cues may be incorporated to improve gait retraining outcomes.
Regulation of AMPAR trafficking in synaptic plasticity by BDNF and the impact of neurodegenerative disease

Research demonstrates that the neural mechanisms underlying synaptic plasticity and learning and memory involve mobilization of AMPA‐type neurotransmitter receptors at glutamatergic synaptic contacts, and that these mechanisms are targeted during neurodegenerative disease. Strengthening neural transmission occurs with insertion of α‐amino‐3‐hydroxy‐5‐methyl‐4‐isoxazolepropionic acid receptors (AMPARs) into synapses while weakening results from receptor withdrawal. A key player in the trafficking of AMPARs during plasticity and learning is the brain‐derived neurotrophic factor (BDNF) signaling system. BDNF is a neurotrophic factor that supports neuronal growth and is required for learning and memory. Significantly, a primary feature of many neurodegenerative diseases is a reduction in BDNF protein as well as disrupted neuronal surface expression of synaptic AMPARs. The resulting weakening of synaptic contacts leads to synapse loss and neuronal degeneration that underlies the cognitive impairment and dementia observed in patients with progressive neurodegenerative disease such as Alzheimer’s. In the face of these data, one therapeutic approach is to increase BDNF bioavailability in brain. While this has been met with significant challenges, the results of the research have been promising. In spite of this, there are currently no clinical trials to test many of these findings on patients. Here, research showing that BDNF drives AMPARs to synapses, AMPAR trafficking is essential for synaptic plasticity and learning, and that neurodegenerative disease results in a significant decline in BDNF will be reviewed. The aim is to draw attention to the need for increasing patient‐directed clinical studies to test the possible benefits of increasing levels of neurotrophins, specifically BDNF, to treat brain disorders. Much is known about the cellular mechanisms that underlie learning and memory in brain. It can be concluded that signaling by neurotrophins like BDNF and AMPA‐type glutamate receptor synaptic trafficking are fundamental to these processes. Data from animal models and patients reveal that these mechanisms are adversely targeted during neurodegenerative disease and results in memory loss and cognitive decline. A brief summary of our understanding of these mechanisms indicates that it is time to apply this knowledge base directly to development of therapeutic treatments that enhance neurotrophins for brain disorders in patient populations.
Effects of mood on self-regulating physical activity and sweets intake within obesity treatments

Background: Although emotional eating is associated with obesity in women, psychological correlates of their treatment-based weight-reduction behaviors are unclear. Aim: To test new model-based propositions of effects of mood on self-regulating physical activity and eating to inform interventions. Methods: Women in community-based obesity treatments with emphases on either self-regulation (n = 56) or weight-management education (n = 54) were assessed on psychological and behavioral variables over 12 months. Results: Emotional eating scores were significantly higher than general samples. Overall significant improvements were found in physical activity- and eating-related self-regulation, mood, physical activity, and sweets consumption. Improvements were more pronounced in the self-regulation-emphasis group. Mood significantly moderated self-regulation-behavior change relationships. Increased physical activity predicted improved mood. Discussion: Findings (a) suggested propensities for emotional eating in women with obesity seeking behavioral treatment, (b) clarified treatment effects and the effect of mood in the self-regulation of physical activity and eating behaviors, and (c) supported model-based treatment targets.
Prognosticating outcome using magnetic resonance imaging in patients with moderate to severe traumatic brain injury: a machine learning approach

ABSTRACT Introduction Over the last decade advancements in computer processing have enabled the application of machine learning (ML) to complex medical problems. Convolutional neural networks (CNN), a type of ML, have been used to interrogate medical images for variety of purposes. In this study, we aimed to investigate the potential application of CNN in prognosticating patients with traumatic brain injury (TBI). Methods Patients with moderate to severe TBI and evidence of diffuse axonal injury (DAI) were selected retrospectively. A CNN model was developed using a training subgroup and a holdout subgroup was used as a testing dataset. We reported the model characteristics including area under the receiver operating characteristic curve (AUC). Results We included a total of 38 patient, of which we generated 725 MRI sections. We developed a CNN model based on a modified AlexNet architecture that interpreted the brain stem injury to generate outcome predictions. The model was able to predict GOS outcomes with a specificity of 0.43 and a sensitivity of 0.997. It showed an AUC of 0.917. Conclusion The utilization of machine learning MRI analysis for prognosticating patients with TBI is a valued method that require further investigation. This will require multicentre collaboration to generate large datasets.
Validity, internal consistency, and responsiveness of the Turkish version of The Family Needs Questionnaire-Revised

ABSTRACT Objective The aim of this study is to conduct validity (language, content and confirmatory factor), internal consistency and responsiveness properties for Turkish version of the Family Needs Questionnaire-Revised (FNQ-R). Methods It was carried out with 185 family members who met study inclusion criteria and provided care for the patients with TBI. Sociodemographic characteristics form and the FNQ-R were used as data collection tools. Validity was assessed by language validity, content validity and confirmatory factor analysis. Internal consistency and item-total correlation were used for reliability analysis. Responsiveness analyses were evaluated with infit and outfit statistics, person–item maps and point biserial correlation. Results The language validity of FNQ-R was provided by translation-back translation. The content validity index values were above 0.80. Fit indices were at an acceptable level in confirmatory factor analysis. Cronbach alpha of subscales was found to be between 0.69 and 0.85 and Spearman–Brown split-half reliability was between 0.68 and 0.85. A positive and significant relationship was found between the subscales. The item fit statistics were at the acceptable level. Conclusion It has been determined that the FNQ-R is a valid and reliable measurement tool to identify the needs of the family members who provide care to patient with traumatic brain injury and can be used for Turkish population.