Combined quantitative amyloid-ß PET and structural MRI features improve Alzheimer's Disease classification in random forest model - A multicenter study.

RATIONALE AND OBJECTIVES: Prior to clinical presentations of Alzheimer's Disease (AD), neuropathological changes, such as amyloid-ß and brain atrophy, have accumulated at the earlier stages of the disease. The combination of such biomarkers assessed by multiple modalities commonly improves the likelihood of AD etiology. We aimed to explore the discriminative ability of Aß PET features and whether combining Aß PET and structural MRI features can improve the classification performance of the machine learning model in older healthy control (OHC) and mild cognitive impairment (MCI) from AD. MATERIAL AND METHODS: We collected 94 AD patients, 82 MCI patients, and 85 OHC from three different cohorts. 17 global/regional Aß features in Centiloid, 122 regional volume, and 68 regional cortical thickness were extracted as imaging features. Single or combined modality features were used to train the random forest model on the testing set. The top 10 features were sorted based on the Gini index in each binary classification. RESULTS: The results showed that AUC scores were 0.81/0.86 and 0.69/0.68 using sMRI/Aß PET features on the testing set in differentiating OHC and MCI from AD. The performance was improved while combining two-modality features with an AUC of 0.89 and an AUC of 0.71 in two classifications. Compared to sMRI features, particular Aß PET features contributed more to differentiating AD from others. CONCLUSION: Our study demonstrated the discriminative ability of Aß PET features in differentiating AD from OHC and MCI. A combination of Aß PET and structural MRI features can improve the RF model performance.

Computer-assisted patient identification tool in inborn errors of metabolism - potential for rare disease patient registry and big data analysis.

BACKGROUND: Patient registries are crucial for rare disease management. However, manual registry construction is labor-intensive and often not user-friendly. Our goal is to establish Hong Kong's first computer-assisted patient identification tool for rare diseases, starting with inborn errors of metabolism (IEM). METHODS: Patient data from 2010 to 2019 was retrieved from electronic databases. Through big data analytics, patient data were filtered based on specific IEM-related biochemical and genetic tests. Clinical notes were analyzed using a rule-based natural language processing technique called regular expression. The algorithm classified each extracted paragraph as "IEM-related" or "not IEM-related." Pathologists reviewed the paragraphs for curation, and the algorithm's performance was evaluated. RESULTS: Out of 46,419 patients with IEM-related tests, the algorithm identified 100 as "IEM-related." After pathologists' validation, 96 cases were confirmed as true IEM, with 1 uncertain case and 3 false positives. A secondary ascertainment yielded a sensitivity of 92.3% compared to our previously published IEM cohort. CONCLUSIONS: Our artificial intelligence approach provides a novel method to identify IEM patients, facilitating the creation of a centralized, computer-assisted rare disease patient registry at the local and national levels. This data can potentially be accessed by multiple stakeholders for collaborative research and to enhance healthcare management for rare diseases.

Knowledge, attitude, and practice toward herpes zoster (HZ) and HZ vaccination: Concept elicitation findings from a multi-country study in the Asia Pacific.

Herpes zoster (HZ) is a prevalent disease characterized by a painful rash. A multi­country study was conducted to elicit public and physician knowledge, attitude, and practice (KAP) toward HZ disease and vaccination for the assessment of local factors influencing HZ vaccine perceptions in four Asian-Pacific countries/territories One-to-one qualitative interviews were conducted in 2022, among the public (people aged ≥ 50 years, adults with parents aged ≥ 50 years, zoster vaccine live-vaccinated individuals aged ≥ 50 years in Republic of Korea, and HZ patients; n = 78) and physicians (general practitioners and specialists; n = 24). Themes surrounding KAP toward HZ and HZ vaccination were summarized using a thematic analysis. A substantial knowledge gap related to HZ was observed among the public, including its causes, long-term impacts, and the at-risk population. There was a low perceived risk of HZ and low general awareness of HZ vaccine availability, although country/territory-specific differences existed. Fear of HZ-associated pain contributed toward vaccination intent among HZ patients and adults with parents aged ≥ 50 years. HZ-naïve adults who were encouraged to receive the vaccine by others were not motivated to do so due to optimism bias. Physicians were perceived to be a reliable source of information. However, physicians did not always proactively discuss HZ vaccination due to time constraints and a perceived need to prioritize other vaccinations including influenza and pneumococcal vaccines. Initiatives are needed to improve public awareness of HZ and its complications, in terms of overall impact on individuals and society, and highlight the important role of physicians in recommending vaccination.

Managing open loop water resource value chain through IoT focused decision and information integration (DII) modelling using fuzzy MCDM approach.

Water is a limited and invaluable resource that is essential for human survival. Negligence and unregulated water use have brought about a global water crisis. Proper management with a relevant decision and information integration approach can aid water to continue as a renewable resource. The water and wastewater industry must shift from outmoded, inefficient techniques to more sustainable, data-driven solutions to address water concerns and improve public health. The Internet of Things (IoT) has emerged as an innovative strategy for decision and information integration to drive an open-loop Water Value Chain (WVC) efficiently. The IoT-driven network allows objects to connect and communicate, gather data in real-time, analyze data and develop reasonable decision - making insights instantaneously. This study aims to find the enablers of IoT for an open-loop WVC. It examines 25 factors for IoT implementation in the open-loop WVC. The 25 factors are clustered into seven enablers using Principal Component Analysis (PCA). These principal components are analyzed by employing a Multi-Criteria Decision Making (MCDM) approach, i.e., the Fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL), which helps to find the cause-effect relationship to prioritize the enablers. The fuzzy set theory is used to address the uncertainty and vagueness in experts' opinions and data deficiency problems. The study reveals that the Ecosystem of an IoT network, IoT network configuration and adaptation and data mobility in an IoT network are the most prominent enablers to consider for the implementation of IoT in an open loop WVC. The study may be helpful for regulatory agencies and enterprises in water distribution and processing for identifying and prioritizing the potential enablers of IoT in an open-loop WVC.

A mHealth-Supported Volunteer-Assisted Spiritual Well-Being Intervention for Discharged Older Patients: A Tripartite Collaboration.

Spiritual well-being (SWB) is a key construct in a holistic health model. This study applied a theory-driven mobile health-supported volunteer-assisted self-help (mVS) intervention to enhance SWB for discharged older patients through a medical-social-academia tripartite collaboration. This study followed a quasi-experimental design, conducted from 2017 to 2019. Data were collected from pre- and post-intervention assessment and Clinical Management System under the Hospital Authority in Hong Kong. SWB was assessed by the Spirituality Scale for Chinese Elders with seven domains, a validated scale suitable for the non-religious context. A total of 161 discharged older patients were recruited, 101 received the mVS intervention and 60 received standardized usual volunteer visits. mVS intervention was assisted by volunteers supported by a corresponding mobile application Fu Le Man Xin. The final analysis included 137 older patients living in Hong Kong aged 61 to 94 years. Repeated measures ANOVA showed mVS intervention significantly enhanced two domains of SSCE: meaning of life (F(1, 64) = 4.029, p = .049) and relationship with others (F(1, 57) = 6.428, p = .014). This study shows that mVS intervention is a feasible medical-social-academia tripartite collaboration that improves two domains of the SWB of discharged older patients: meaning of life and relationship with others.

Modeling the decision of ridesourcing drivers to park and wait at trip ends: a comparison between Perth, Australia and Kolkata, India.

It is often difficult for the ridesourcing drivers to get a trip immediately after dropping off a passenger. The main objective of the drivers is to increase their income by serving more trips. The most prominent options available to the drivers after reaching passengers' destinations are: (a) park and wait in and around their drop-off location, (b) cruise in and around their drop-off location and (c) drive to another location to receive trip requests quickly. Previous studies were conducted to understand the driver behaviour in a taxi and other similar services. However, the perception of ridesourcing drivers on parking and waiting after dropping off passengers is yet to be explored. The drivers' decision on waiting can affect users' waiting time, the number of matched trips by the TNCs, and parking spaces in the city. Moreover, drivers' waiting time tolerance can also impact other drivers' total number of trips, total earnings, total distance travelled in the city, and fleet size. The aim of this study is to understand the influence of drivers' characteristics on drivers' decision to park and wait after dropping off a passenger. This study estimates and compares the waiting time tolerance of the ridesourcing drivers using a zero-inflated cox spline model between Perth and Kolkata. It is observed that drivers in Kolkata have higher waiting time tolerance than Perth drivers. Moreover, the drivers in both the cities are more likely to wait at high-demand areas urging the urban authorities to determine spatio-temporal parking demand to design the parking infrastructure for such areas.

The fractional amplitude of low-frequency fluctuations signals related to amyloid uptake in high-risk populations-A pilot fMRI study.

Background: Patients with type 2 diabetes mellitus (T2DM) and subjective cognitive decline (SCD) have a higher risk to develop Alzheimer's Disease (AD). Resting-state-functional magnetic resonance imaging (rs-fMRI) was used to document neurological involvement in the two groups from the aspect of brain dysfunction. Accumulation of amyloid-ß (Aß) starts decades ago before the onset of clinical symptoms and may already have been associated with brain function in high-risk populations. However, this study aims to compare the patterns of fractional amplitude of low-frequency fluctuations (fALFF) maps between cognitively normal high-risk groups (SCD and T2DM) and healthy elderly and evaluate the association between regional amyloid deposition and local fALFF signals in certain cortical regions. Materials and methods: A total of 18 T2DM, 11 SCD, and 18 healthy elderlies were included in this study. The differences in the fALFF maps were compared between HC and high-risk groups. Regional amyloid deposition and local fALFF signals were obtained and further correlated in two high-risk groups. Results: Compared to HC, the altered fALFF signals of regions were shown in SCD such as the left posterior cerebellum, left putamen, and cingulate gyrus. The T2DM group illustrated altered neural activity in the superior temporal gyrus, supplementary motor area, and precentral gyrus. The correlation between fALFF signals and amyloid deposition was negative in the left anterior cingulate cortex for both groups. In the T2DM group, a positive correlation was shown in the right occipital lobe and left mesial temporal lobe. Conclusion: The altered fALFF signals were demonstrated in high-risk groups compared to HC. Very early amyloid deposition in SCD and T2DM groups was observed to affect the neural activity mainly involved in the default mode network (DMN).

Leveraging AI for advanced analytics to forecast altered tourism industry parameters: A COVID-19 motivated study.

COVID-19 pandemic has given a sudden shock to economy indices worldwide and especially to the tourism sector, which is already very sensitive to such crises as natural calamities, terrorist activities, virus outbreaks and unwanted conditions. The economic implications for a reduction in tourism demand, and the need to analyse post-COVID-19 tourism motivates our research. This study aims to forecast the future trends for foreign tourist arrivals and foreign exchange earnings for India and to formulate a model to predict the future trends based on the COVID-19 parameters, vaccinations and stringency index (Government travelling guidelines). In the study, we have developed artificial intelligence models (random forest, linear regression) using the stacked based ensemble learning method for the development of base models and meta models for the study of COVID-19 and its effect on the tourism industry. The architecture of a stacking model consists of two or more base models, often referred to as level-0 models, and a meta-model that combines the predictions of the base models, and is referred to as a level-1 model (Smyth & Wolpert, 1999). The results show that the projected losses require quick action on developing new practices to sustain and complement the resilience of tourism per se.

Incremental diagnostic value of 18F-Fluetemetamol PET in differential diagnoses of Alzheimer's Disease-related neurodegenerative diseases from an unselected memory clinic cohort.

To evaluate the incremental diagnostic value of 18F-Flutemetamol PET following MRI measurements on an unselected prospective cohort collected from a memory clinic. A total of 84 participants was included in this study. A stepwise study design was performed including initial analysis (based on clinical assessments), interim analysis (revision of initial analysis post-MRI) and final analysis (revision of interim analysis post-18F-Flutemetamol PET). At each time of evaluation, every participant was categorized into SCD, MCI or dementia syndromal group and further into AD-related, non-AD related or non-specific type etiological subgroup. Post 18F-Flutemetamol PET, the significant changes were seen in the syndromal MCI group (57%, p < 0.001) involving the following etiological subgroups: AD-related MCI (57%, p < 0.01) and non-specific MCI (100%, p < 0.0001); and syndromal dementia group (61%, p < 0.0001) consisting of non-specific dementia subgroup (100%, p < 0.0001). In the binary regression model, amyloid status significantly influenced the diagnostic results of interim analysis (p < 0.01). 18F-Flutemetamol PET can have incremental value following MRI measurements, particularly reflected in the change of diagnosis of individuals with unclear etiology and AD-related-suspected patients due to the role in complementing AD-related pathological information.

An extended multi-criteria group decision-making method with psychological factors and bidirectional influence relation for emergency medical supplier selection.

The COVID-19 pandemic outbreak spread rapidly worldwide, posing a severe threat to human life. Due to its unpredictability and destructiveness, the emergency has aroused great common in society. At the same time, the selection of emergency medical supplier is one of the critical links in emergency decision-making, so undertaking appropriate decision-making using scientific tools becomes the primary challenge when an emergency outbreak occurs. The multi criteria group decision-making (MCGDM) method is an applicable and common method for choosing supplier. Nevertheless, because emergency medical supplier selection should consider regarding many aspects, it is difficult for decision makers (DMs) to develop a comprehensive assessment method for emergency medical supplier. Therefore, few academics have focused on emergency situation research by the MCGDM method, and the existing MCGDM method has some areas for improvement. In view of this situation, in this study, we propose a new MCGDM method, which considers the bidirectional influence relation of the criteria, consensus and the psychological factors of DMs. It providers a good aid in emergency decision-making and it could apply to other types of MCGDM research. Firstly, DMs give their assessment in interval type-2 fuzzy sets (IT2FSs). Secondly, an extended IT2FSs assessment method and a novel ISM-BWM-Cosine Similarity-Max Deviation Method (IBCSMDM) are used for weighing all alternatives. The TODIM (an acronym for interactive and multi-criteria decision-making in Portuguese) can obtain the ranking results under different risk attenuation factors. Eventually, this extended IT2FSs-IBCSMDM-TODIM method is applied in a real case in Wuhan in the context of COVID-19 to illustrate the practicability and usefulness.

Reduced Pneumonia Risk in Advanced Dementia Patients on Careful Hand Feeding Compared With Nasogastric Tube Feeding.

OBJECTIVES: To compare survival and pneumonia risk among hospitalized patients with advanced dementia on nasogastric tube feeding (NGF) vs careful hand feeding (CHF) and to examine outcomes by feeding problem type. DESIGN: Retrospective cohort study. SETTING AND PARTICIPANTS: Advanced dementia patients aged ≥60 years with indication for tube feeding admitted to 2 geriatric convalescent hospitals between January 1, 2015, and June 30, 2019. METHODS: Comparison on the effect of NGF and CHF on survival and pneumonia risk using Kaplan Meier survival analysis and Cox proportional hazards models. RESULTS: Of the 764 patients (mean age 89 years, 61% female, 74% residential care home residents), 464 (61%) were initiated on NGF and 300 (39%) on CHF. The primary feeding problem types were dysphagia (50%), behavioral feeding problem (33%), or both (17%). There was no difference in 1-year survival rate between NGF and CHF groups (36% vs 37%, P = .71) and survival did not differ by feeding problem type. Nasogastric tube feeding was not a significant predictor for survival (adjusted hazard ratio 1.15, 95% CI 0.94-1.39). Among 577 (76%) patients who survived to discharge, pneumonia rates were lower in the CHF group (48% vs 60%, P = .004). After adjusting for cofounders, NGF was a significant risk factor for pneumonia (adjusted hazard ratio 1.41, 95% CI 1.08-1.85). In subgroup analyses, NGF was associated with increased pneumonia risk for patients with both dysphagia and behavioral feeding problem (P = .01) but not in patients with behavioral feeding problem alone (P = .24) or dysphagia alone (P = .30). CONCLUSIONS AND IMPLICATIONS: For advanced dementia patients with feeding problems, there is no difference in survival between NGF and CHF. However, NGF is associated with a higher pneumonia risk, particularly for patients with both dysphagia and behavioral feeding problem. Further research on how the feeding problem type impacts pneumonia risk for patients on NGF is needed.

Can a higher endometrial thickness threshold exclude endometrial cancer and atypical hyperplasia in asymptomatic postmenopausal women? A systematic review.

BACKGROUND: Asymptomatic postmenopausal women incidentally found to have thickened endometrium (>4 mm) on transvaginal ultrasound (TVUS) often undergo hysteroscopy and dilatation and curettage despite having a low absolute risk of endometrial cancer. A low threshold for investigation may be unnecessary in these women. AIM: This systematic literature review examines whether an increased TVUS endometrial thickness threshold has superior diagnostic accuracy for endometrial malignancies and premalignancies in asymptomatic postmenopausal women than the current threshold of ≥4 mm. METHODS: Pubmed, EMBASE and Cochrane Database of Systematic Reviews were systematically searched using keywords for publications between 2011 and 2021. Studies were included if they reported TVUS endometrial thickness analysis in asymptomatic postmenopausal women and excluded if they were written in a non-English language. Quality of evidence in the included articles was evaluated according to recommendations by the Grading of Recommendations Assessment Development and Evaluation Working Group and reported results were tabulated. RESULTS: Of seven studies (N = 2986), better evidence identified 12 mm as the optimal diagnostic threshold (area under the curve receiver operating characteristic (AUC ROC) 0.716, 95% CI 0.534-0.897, P = 0.019) for endometrial cancer in asymptomatic postmenopausal women. Two higher quality studies (n = 488 and n = 4751) identified 11 mm as optimal for diagnosing both endometrial carcinoma and atypical hyperplasia (AUC ROC 0.587, 95% CI 0.465-0.708, P = 0.144 and 2.59 relative risk, 95% CI 1.66-4.05, P < 0.001). CONCLUSION: Evidence for improved detection of endometrial premalignancies and malignancies using alternative endometrial thickness thresholds is not rigorous. Evidence for improved outcomes using alternative thresholds is inadequate. Observation of asymptomatic postmenopausal women without risk factors and with an endometrial thickness of less than 10 mm may be reasonable.

Effectiveness of a Two-Tier Family-Oriented Intervention in Enhancing the Family Functioning and Care Capacity of the Family Caregivers of Stroke Survivors: Protocol for a Randomized Controlled Trial.

BACKGROUND: Stroke has profound impacts on families. Often, family members, including stroke survivors and the person who takes up the role of the primary caregiver, would encounter demands on finances, rehabilitation arrangement, and even conflicts. Hence, a family-oriented intervention is expected to enable families to rebuild internal and external resources to achieve optimal rehabilitation and community reintegration. OBJECTIVE: This study aims to describe a design of a two-tier family-oriented care management intervention for enhancing the family functioning and care capacity of the caregivers of stroke survivors. METHODS: The two-tier care management intervention was guided by a standardized protocol conducted by trained professional care managers (first tier) with the support of trained volunteers (second tier), which lasted for 8-12 weeks. Participants were recruited through collaborating hospitals according to inclusion and exclusion criteria. In order to examine the effectiveness and cost-effectiveness of the two-tier care management intervention, a two-arm randomization multicenter study was designed, including an active comparison group, which was guided by a standardized protocol conducted by trained volunteers. Dyadic participants, including both stroke survivors and their primary caregivers for both groups, were invited to participate in a questionnaire survey using standardized and purposefully developed measures 3 times: before the intervention, immediately after the intervention, and 2 months after the intervention. The primary outcome was family functioning measured by the Family Role Performance Scale and Family Assessment Device-General Functioning Scale. The secondary outcomes included caregiving burden, depressive symptoms, care management strategies, and the incremental cost-effectiveness ratio. RESULTS: Recruitment began in January 2017 and was completed at the end of April 2019. Data collection was completed at the end of March 2020. As of March 2020, enrollment has been completed (n=264 stroke caregivers). A total of 200 participants completed the baseline questionnaires. We aim to publish the results by mid-2021. CONCLUSIONS: This study successfully developed a two-tier care management protocol that aims to enhance the family functioning of the caregivers of stroke survivors. Guided by a standardized protocol, this family-oriented two-tier intervention protocol was found to be feasible among Chinese families. TRIAL REGISTRATION: ClinicalTrials.gov NCT03034330; https://ichgcp.net/clinical-trials-registry/NCT03034330. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR1-10.2196/16703.

Molecular regulation of brain metabolism underlying circadian epilepsy.

Extensive study has demonstrated that epilepsy occurs with greater frequency at certain times in the 24-h cycle. Although these findings implicate an overlap between the circadian rhythm and epilepsy, the molecular and cellular mechanisms underlying this circadian regulation are poorly understood. Because the 24-h rhythm is generated by the circadian molecular system, it is not surprising that this system comprised of many circadian genes is implicated in epilepsy. We summarized evidence in the literature implicating various circadian genes such as Clock, Bmal1, Per1, Rev-erb⍺, and Ror⍺ in epilepsy. In various animal models of epilepsy, the circadian oscillation and the steady-state level of these genes are disrupted. The downstream pathway of these genes involves a large number of metabolic pathways associated with epilepsy. These pathways include pyridoxal metabolism, the mammalian target of rapamycin pathway, and the regulation of redox state. We propose that disruption of these metabolic pathways could mediate the circadian regulation of epilepsy. A greater understanding of the cellular and molecular mechanism of circadian regulation of epilepsy would enable us to precisely target the circadian disruption in epilepsy for a novel therapeutic approach.

Heterogeneity of Amyloid Binding in Cognitively Impaired Patients Consecutively Recruited from a Memory Clinic: Evaluating the Utility of Quantitative 18F-Flutemetamol PET-CT in Discrimination of Mild Cognitive Impairment from Alzheimer's Disease and Other Dementias.

BACKGROUND: With the more widespread use of 18F-radioligand-based amyloid-ß (Aß) PET-CT imaging, we evaluated Aß binding and the utility of neocortical 18F-Flutemetamol standardized uptake value ratio (SUVR) as a biomarker. OBJECTIVE: 18F-Flutemetamol SUVR was used to differentiate 1) mild cognitive impairment (MCI) from Alzheimer's disease (AD), and 2) MCI from other non-AD dementias (OD). METHODS: 109 patients consecutively recruited from a University memory clinic underwent clinical evaluation, neuropsychological test, MRI and 18F-Flutemetamol PET-CT. The diagnosis was made by consensus of a panel consisting of 1 neuroradiologist and 2 geriatricians. The final cohort included 13 subjective cognitive decline (SCD), 22 AD, 39 MCI, and 35 OD. Quantitative analysis of 16 region-of-interests made by Cortex ID software (GE Healthcare). RESULTS: The global mean 18F-Flutemetamol SUVR in SCD, MCI, AD, and OD were 0.50 (SD-0.08), 0.53 (SD-0.16), 0.76 (SD-0.10), and 0.56 (SD-0.16), respectively, with SUVR in SCD and MCI and OD being significantly lower than AD. Aß binding in SCD, MCI, and OD was heterogeneous, being 23%, 38.5%, and 42.9% respectively, as compared to 100% amyloid positivity in AD. Using global SUVR, ROC analysis showed AUC of 0.868 and 0.588 in differentiating MCI from AD and MCI from OD respectively. CONCLUSION: 18F-Flutemetamol SUVR differentiated MCI from AD with high efficacy (high negative predictive value), but much lower efficacy from OD. The major benefit of the test was to differentiate cognitively impaired patients (either SCD, MCI, or OD) without AD-related-amyloid-pathology from AD in the clinical setting, which was under-emphasized in the current guidelines proposed by Amyloid Imaging Task Force.

Short exposure to hyperoxia causes cultured lung epithelial cell mitochondrial dysregulation and alveolar simplification in mice.

BACKGROUND: Prolonged exposure to high oxygen concentrations in premature infants, although lifesaving, can induce lung oxidative stress and increase the risk of developing BPD, a form of chronic lung disease. The lung alveolar epithelium is damaged by sustained hyperoxia, causing oxidative stress and alveolar simplification; however, it is unclear what duration of exposure to hyperoxia negatively impacts cellular function. METHODS: Here we investigated the role of a very short exposure to hyperoxia (95% O2, 5% CO2) on mitochondrial function in cultured mouse lung epithelial cells and neonatal mice. RESULTS: In epithelial cells, 4 h of hyperoxia reduced oxidative phosphorylation, respiratory complex I and IV activity, utilization of mitochondrial metabolites, and caused mitochondria to form elongated tubular networks. Cells allowed to recover in air for 24 h exhibited a persistent global reduction in fuel utilization. In addition, neonatal mice exposed to hyperoxia for only 12 h demonstrated alveolar simplification at postnatal day 14. CONCLUSION: A short exposure to hyperoxia leads to changes in lung cell mitochondrial metabolism and dynamics and has a long-term impact on alveolarization. These findings may help inform our understanding and treatment of chronic lung disease. IMPACT: Many studies use long exposures (up to 14 days) to hyperoxia to mimic neonatal chronic lung disease. We show that even a very short exposure to hyperoxia leads to long-term cellular injury in type II-like epithelial cells. This study demonstrates that a short (4 h) period of hyperoxia has long-term residual effects on cellular metabolism. We show that neonatal mice exposed to hyperoxia for a short time (12 h) demonstrate later alveolar simplification. This work suggests that any exposure to clinical hyperoxia leads to persistent lung dysfunction.

Robotic-assisted versus conventional laparoscopic hysterectomy for endometrial cancer.

OBJECTIVE: The safety and efficacy of robotic-assisted laparoscopic hysterectomy (RALH) compared with conventional total laparoscopic hysterectomy (TLH) for surgical staging of endometrial cancer has not been clearly established. With the commencement of a robotic program at our institution, our objective was to evaluate and compare the surgical outcomes of RALH with TLH for endometrial cancer. METHODS: A retrospective cohort study was performed on 39 patients who underwent RALH and 41 patients who underwent TLH for endometrial cancer at a tertiary care academic institution. RESULTS: In the setting of endometrial cancer RALH is significantly longer to perform than TLH (mean operating time 133 min vs 107 min, p = 0.0001). There is higher estimated blood loss in TLH cases than RALH cases (78 mL vs 22 mL, p = 0.015). Women who underwent RALH had a shorter length of stay (1.3 days vs 1.8 days, p = 0.006) than TLH patients, and six cases (15 %) of the RALH group were discharged on the same day of surgery. There were no differences between the RALH and TLH groups in intraoperative or postoperative complications and there were no conversions to laparotomy. CONCLUSION: RALH is safe and feasible for the treatment of endometrial cancer, with low morbidity, less blood loss and shorter length of stay than TLH. RALH is associated with longer mean operating times than TLH and this may improve with enlisting a consistent experienced team. Prospective randomised studies which include analysis of quality of life measures and long-term outcomes are required to further establish the role of RALH in the surgical staging of endometrial cancer.

Data Analytics for Predicting COVID-19 Cases in Top Affected Countries: Observations and Recommendations.

The outbreak of the 2019 novel coronavirus disease (COVID-19) has adversely affected many countries in the world. The unexpected large number of COVID-19 cases has disrupted the healthcare system in many countries and resulted in a shortage of bed spaces in the hospitals. Consequently, predicting the number of COVID-19 cases is imperative for governments to take appropriate actions. The number of COVID-19 cases can be accurately predicted by considering historical data of reported cases alongside some external factors that affect the spread of the virus. In the literature, most of the existing prediction methods focus only on the historical data and overlook most of the external factors. Hence, the number of COVID-19 cases is inaccurately predicted. Therefore, the main objective of this study is to simultaneously consider historical data and the external factors. This can be accomplished by adopting data analytics, which include developing a nonlinear autoregressive exogenous input (NARX) neural network-based algorithm. The viability and superiority of the developed algorithm are demonstrated by conducting experiments using data collected for top five affected countries in each continent. The results show an improved accuracy when compared with existing methods. Moreover, the experiments are extended to make future prediction for the number of patients afflicted with COVID-19 during the period from August 2020 until September 2020. By using such predictions, both the government and people in the affected countries can take appropriate measures to resume pre-epidemic activities.

Emissions and health risks from the use of 3D printers in an occupational setting.

The aim of this study was to determine concentrations of particulates and volatile organic compounds (VOCs) emitted from 3D printers using polylactic acid (PLA) filaments at a university workroom to assess exposure and health risks in an occupational setting. Under typical-case (one printer) and worst-case (three printers operating simultaneously) scenarios, particulate concentration (total and respirable), VOCs and formaldehyde were measured. Air samples were collected in the printing room and adjacent hallway. Size-resolved levels of nano-diameter particles were also collected in the printing room. Total particulate levels were higher in the worst-case scenario (0.7 mg/m3) vs. typical-case scenario (0.3 mg/m3). Respirable particulate and formaldehyde concentrations were similar between the two scenarios. Size-resolved measurements showed that most particles ranged from approximately 27 to 116 nm. Total VOC levels were approximately 6-fold higher during the worst-case scenario vs. typical situation with isopropyl alcohol being the predominant VOC. Airborne concentrations in the hallway were generally lower than inside the printing room. All measurements were below their respective occupational exposure limits. In summary, emissions of particulates and VOCs increased when multiple 3D printers were operating simultaneously. Airborne levels in the adjacent hallway were similar between the two scenarios. Overall, data suggest a low risk of significant and persistent adverse health effects. Nevertheless, the health effects attributed to 3D printing are not fully known and adherence to good hygiene principles is recommended during use of this technology.