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Adult intussusceptions are a rare cause of abdominal obstruction and are usually associated with a neoplastic disease; idiopathic forms are extremely rare. We report a case of enterocolic intussusception in a young woman who experienced symptoms of abdominal obstruction. Imaging findings were reported. On histological examination, no underlying diseases were found. The patient presented at the hospital for computed tomography because of persistent abdominal pain. Computed tomography revealed an enterocolic invagination involving the ileocecal valve and cecum and widespread edematous thickening of the colonic parietal walls. Idiopathic enterocolic intussusception is an uncommon abdominal urgency in adults. Symptoms can be vague and persistent, delaying an accurate diagnosis. Imaging is crucial in these circumstances to make a diagnosis. Some computed tomography findings, such as a target-like bulk, may be suggestive.

Objectives: We investigated the holistic experiences of university students during the pandemic. Participants: Thirty-eight students in a public university system in New York City (NYC) purposively selected from neighborhoods highly affected by the pandemic based on level of self-reported impact. Methods: We conducted virtual in-depth interviews from May to August 2021 and analyzed data using thematic coding and constant comparison techniques informed by grounded theory. Results: Financial and social support systems, such as governmental and school resources, were critical to addressing essential needs and allowing students to persist. For those whose essential needs were met, faculty members' flexibility and students' experience with online learning were central to their academic success. Conclusions: Institutions of higher education should strengthen financial and social support systems to meet students' essential needs. Academic policies to bolster online pedagogy and faculty's flexibility can facilitate student retention and completion.

Abstract Background Multimorbidity (MM) is generally defined as the presence of 2 or more chronic diseases in the same patient and seems to be frequently associated with frailty and poor quality of life. However, the complex interplay between MM and functional status in hospitalized older patients has not been fully elucidated so far. Here, we implemented a 2-step approach, combining cluster analysis and association rule mining to explore how patterns of MM and disease associations change as a function of disability. Methods This retrospective cohort study included 3366 hospitalized older patients discharged from acute care units of Ancona and Cosenza sites of Italian National Institute on Aging (INRCA-IRCCS) between 2011 and 2017. Cluster analysis and association rule mining (ARM) were used to explore patterns of MM and disease associations in the whole population and after stratifying by dependency in activities of daily living (ADL) at discharge. Sensitivity analyses in men and women were conducted to test for robustness of study findings. Results Out of 3366 included patients, 78% were multimorbid. According to functional status, 22.2% of patients had no disability in ADL (functionally independent group), 22.7% had 1 ADL dependency (mildly dependent group), and 57.4% 2 or more ADL impaired (moderately-severely dependent group). Two main MM clusters were identified in the whole general population and in single ADL groups. ARM revealed interesting within-cluster disease associations, characterized by high lift and confidence. Specifically, in the functionally independent group, the most significant ones involved atrial fibrillation (AF)-anemia and chronic kidney disease (CKD) (lift = 2.32), followed by coronary artery disease (CAD)-AF and heart failure (HF) (lift = 2.29); in patients with moderate-severe ADL disability, the most significant ARM involved CAD-HF and AF (lift = 1.97), thyroid dysfunction and AF (lift = 1.75), cerebrovascular disease (CVD)-CAD and AF (lift = 1.55), and hypertension-anemia and CKD (lift = 1.43). Conclusions Hospitalized older patients have high rates of MM and functional impairment. Combining cluster analysis to ARM may assist physicians in discovering unexpected disease associations in patients with different ADL status. This could be relevant in the view of individuating personalized diagnostic and therapeutic approaches, according to the modern principles of precision medicine.

Abstract Introduction The aim of this work is to estimate the sensitivity, specificity, and misclassification rate of an automated retinal image analysis system (ARIAS) in diagnosing active diabetic macular edema (DME) and to identify factors associated with true and false positives. Methods We conducted a cross-sectional study of prospectively enrolled patients with diabetes mellitus (DM) referred to a tertiary medical retina center for screening or management of DME. All patients underwent two-field fundus photography (macula- and disc-centered) with a true-color confocal camera; images were processed by EyeArt V.2.1.0 (Woodland Hills, CA, USA). Active DME was defined as the presence of intraretinal or subretinal fluid on spectral-domain optical coherence tomography (SD-OCT). Sensitivity and specificity and their 95% confidence intervals (CIs) were calculated. Variables associated with true (i.e., DME labeled as present by ARIAS + fluid on SD-OCT) and false positives (i.e., DME labeled as present by ARIAS + no fluid on SD-OCT) of active DME were explored. Results A total of 298 eyes were included; 92 eyes (31%) had active DME. ARIAS sensitivity and specificity were 82.61% (95% CI 72.37–89.60) and 84.47% (95% CI 78.34–89.10). The misclassification rate was 16%. Factors associated with true positives included younger age (p = 0.01), shorter DM duration (p = 0.006), presence of hard exudates (p = 0.005), and microaneurysms (p = 0.002). Factors associated with false positives included longer DM duration (p = 0.01), worse diabetic retinopathy severity (p = 0.008), history of inactivated DME (p

Abstract Remdesivir (RDV) was the first Food and Drug Administration (FDA)-approved medication for COVID-19, with discordant data on efficacy in reducing mortality risk and disease progression. In the context of a dynamic and rapidly changing pandemic landscape, the utilization of real-world evidence is of utmost importance. The objective of this study is to evaluate the impact of RDV on patients who have been admitted to two university referral hospitals in Italy due to COVID-19. All patients older than 18 years and hospitalized at two different universities (Bari and Palermo) were enrolled in this study. To minimize the effect of potential confounders, we used propensity score matching with one case (Remdesivir) and one control that never experienced this kind of intervention during hospitalization. Mortality was the primary outcome of our investigation, and it was recorded using death certificates and/or medical records. Severe COVID-19 was defined as admission to the intensive care unit or a qSOFAscore ≥ 2 or CURB65scores ≥ 3. After using propensity score matching, 365 patients taking Remdesivir and 365 controls were included. No significant differences emerged between the two groups in terms of mean age and percentage of females, while patients taking Remdesivir were less frequently active smokers (p

Objective The growing attention towards the psychosocial characteristics of mild cognitive impairment (MCI), a possible prodromal stage of dementia, contributed to the spread of patient-centered approaches to the care of age-related cognitive decline. Within these new care models, including Case-Management approaches, technology-based treatments showed to improve quality of life and psychosocial functioning of people with MCI. However, studies testing technologies to treat functional well-being of MCI patients are still few. Moreover, whether Case Manager supervised or unsupervised technological interventions lead to comparable results is so far unexplored. This study protocol aims to test the superiority of a 1-year physical and cognitive training treatment supervised by a Case Manager in improving the quality of life, functional decline, treatment adherence, cognitive impairment of MCI patients and the mental well-being of informal caregivers compared to the same yet unsupervised treatment. Methods In a multicentric, randomized, two parallel arms controlled clinical trial MCI patients ≥65 year-old will be randomized to receive a technology-based treatment either supervised or unsupervised by a Case Manager. Regardless of the study group, patients will perform cognitive and motor exercises with the monitoring of a specialist only during the first 6 weeks of intervention. Three and two assessment points will be considered during the intervention and follow-up period, respectively. The quality of life will be measured as primary outcome at 6 months after baseline. Conclusions The results of this study will provide an evidence base to use Case Management as an adjuvant approach for technology-based treatments of psychosocial characteristics of MCI.

Chronic kidney disease (CKD) in older individuals is a matter of growing concern in the field of public health across the globe. Indeed, prevalence of kidney function impairment increases with advancing age and is often exacerbated by age-induced modifications of kidney function, presence of chronic diseases such as diabetes, hypertension, and cardiovascular disorders, and increased burden related to frailty, cognitive impairment and sarcopenia. Accurate assessment of CKD in older individuals is crucial for timely intervention and management and relies heavily on biomarkers for disease diagnosis and monitoring. However, the interpretation of these biomarkers in older patients may be complex due to interplays between CKD, aging, chronic diseases and geriatric syndromes. Biomarkers such as serum creatinine, estimated glomerular filtration rate (eGFR), and albuminuria can be significantly altered by systemic inflammation, metabolic changes, and medication use commonly seen in this population. To overcome the limitations of traditional biomarkers, several innovative proteins have been investigated as potential, in this review we aimed at consolidating the existing data concerning the geriatric aspects of CKD, describing the challenges and considerations in using traditional and innovative biomarkers to assess CKD in older patients, highlighting the need for integration of the clinical context to improve biomarkers’ accuracy.

A sample of sexual- and gender-minority students (n = 65; 51.6% female; 55.8% White; M age = 16.94 years) reported more peer victimization, lower academic achievement, and poorer perceptions of school safety as compared to their heterosexual allied peers. Sexual- and gender-minority students demonstrating higher levels of sexual activity and having trouble developing friendships reported increased victimization. Staff and peer supportiveness and anti-bullying enforcement significantly predicted less bullying. Anti-bullying programs containing sexual- and gender-minority-specific language were associated with less bullying of sexual- and gender-minority youth. Positive relationships existed between anti-bullying enforcement and support by school personnel and peers.

Abstract Background Coronavirus disease COVID-19 is a heterogeneous condition caused by SARS-CoV-2 infection. Generally, it is characterized by interstitial pneumonia that can lead to impaired gas-exchange, acute respiratory failure, and death, although a complex disorder of multi-organ dysfunction has also been described. The pathogenesis is complex, and a variable combination of factors has been described in critically ill patients. COVID-19 is a particular risk for older persons, particularly those with frailty and comorbidities. Blood bacterial DNA has been reported in both physiological and pathological conditions and has been associated with some haematological and laboratory parameters but, to date, no study has characterized it in hospitalized old COVID-19 patients The present study aimed to establish an association between blood bacterial DNA (BB-DNA) and clinical severity in old COVID-19 patients. Results BB-DNA levels were determined, by quantitative real-time PCRs targeting the 16S rRNA gene, in 149 hospitalized older patients (age range 65–99 years) with COVID-19. Clinical data, including symptoms and signs of infection, frailty status, and comorbidities, were assessed. BB-DNA was increased in deceased patients compared to discharged ones, and Cox regression analysis confirmed an association between BB-DNA and in-hospital mortality. Furthermore, BB-DNA was positively associated with the neutrophil count and negatively associated with plasma IFN-alpha. Additionally, BB-DNA was associated with diabetes. Conclusions The association of BB-DNA with mortality, immune-inflammatory parameters and diabetes in hospitalized COVID-19 patients suggests its potential role as a biomarker of unfavourable outcomes of the disease, thus it could be proposed as a novel prognostic marker in the assessment of acute COVID-19 disease.

Abstract Background The Neutrophil-to-lymphocyte ratio (NLR) is a marker of poor prognosis in hospitalized older patients with different diseases, but there is still no consensus on the optimal cut-off value to identify older patients at high-risk of in-hospital mortality. Therefore, in this study we aimed at both validating NLR as a predictor of death in older hospitalized patients and assess whether the presence of specific acute diseases can modify its predictive value. Methods This prospective cohort study included 5034 hospitalizations of older patients admitted to acute care units in the context of the ReportAge study. NLR measured at admission was considered as the exposure variable, while in-hospital mortality was the outcome of the study. ROC curves with Youden’s method and restricted cubic splines were used to identify the optimal NLR cut-off of increased risk. Cox proportional hazard models, stratified analyses, and Kaplan–Meier survival curves were used to analyse the association between NLR and in-hospital mortality. Results Both continuous and categorical NLR value (cut-off ≥ 7.95) predicted mortality in bivariate and multivariate prognostic models with a good predictive accuracy. The magnitude of this association was even higher in patients without sepsis, congestive heart failure, and pneumonia, and those with higher eGFR, albumin, and hemoglobin (p

In the tumor microenvironment (TME), ROS production affects survival, progression, and therapy resistance in colorectal cancer (CRC). H2O2-mediated oxidative stress can modulate Wnt/β-catenin signaling and metabolic reprogramming of the TME. Currently, it is unclear how mild/moderate oxidative stress (eustress) modulates Wnt/β-catenin/APC and JNK signaling relationships in primary and metastatic CRC cells. In this study, we determined the effects of the H2O2 concentration inducing eustress on isogenic SW480 and SW620 cells, also in combination with JNK inhibition. We assessed cell viability, mitochondrial respiration, glycolysis, and Wnt/β-catenin/APC/JNK gene and protein expression. Primary CRC cells were more sensitive to H2O2 eustress combined with JNK inhibition, showing a reduction in viability compared to metastatic cells. JNK inhibition under eustress reduced both glycolytic and respiratory capacity in SW620 cells, indicating a greater capacity to adapt to TME. In primary CRC cells, H2O2 alone significantly increased APC, LEF1, LRP6, cMYC and IL8 gene expression, whereas in metastatic CRC cells, this effect occurred after JNK inhibition. In metastatic but not in primary tumor cells, eustress and inhibition of JNK reduced APC, β-catenin, and pJNK protein. The results showed differential cross-regulation of Wnt/JNK in primary and metastatic tumor cells under environmental eustress conditions. Further studies would be useful to validate these findings and explore their therapeutic potential.

Clouds are key to understanding the atmosphere and climate, and a long series of satellite observations provide invaluable information to study their properties. EUMETSAT has published Release 1 of the Optimal Cloud Analysis (OCA) Climate Data Record (CDR), which provides a homogeneous time series of cloud properties of up to two overlapping layers, together with uncertainties. The OCA product is derived using the 15 min Spinning Enhanced Visible and Infrared Imager (SEVIRI) measurements onboard Meteosat Second Generation (MSG) in geostationary orbit and covers the period from 19 January 2004 until 31 August 2019. This paper presents the validation of the OCA cloud-top pressure (CTP) against independent lidar-based estimates and the quality assessment of the cloud optical thickness (COT) and cloud particle effective radius (CRE) against a combination of products from satellite-based active and passive instruments. The OCA CTP is in good agreement with the CTP sensed by lidar for low thick liquid clouds and substantially below in the case of high ice clouds, in agreement with previous studies. The retrievals of COT and CRE are more reliable when constrained by solar channels and are consistent with other retrievals from passive imagers. The resulting cloud properties are stable and homogeneous over the whole period when compared against similar CDRs from passive instruments. For CTP, the OCA CDR and the near-real-time OCA products are consistent, allowing for the use of OCA near-real time products to extend the CDR beyond August 2019.

The Identification, Placement, and Review Committee (IPRC) process has been long established within Ontario special education practice and provincial legislation. Borne out of advocacy for advancing the right to education for children with disabilities, the IPRC process is now being critically explored as to whether the process itself creates an infringement on students' access and rights to quality education. Drawing on historical and contemporary shifts in education policy and human rights in Ontario, this paper presents the case that the current structure of the IPRC is outdated and may function as a significant barrier to students' academic futures.