A machine learning decision criterion for reducing scan time for hyperspectral neutron computed tomography systems.

We present the first machine learning-based autonomous hyperspectral neutron computed tomography experiment performed at the Spallation Neutron Source. Hyperspectral neutron computed tomography allows the characterization of samples by enabling the reconstruction of crystallographic information and elemental/isotopic composition of objects relevant to materials science. High quality reconstructions using traditional algorithms such as the filtered back projection require a high signal-to-noise ratio across a wide wavelength range combined with a large number of projections. This results in scan times of several days to acquire hundreds of hyperspectral projections, during which end users have minimal feedback. To address these challenges, a golden ratio scanning protocol combined with model-based image reconstruction algorithms have been proposed. This novel approach enables high quality real-time reconstructions from streaming experimental data, thus providing feedback to users, while requiring fewer yet a fixed number of projections compared to the filtered back projection method. In this paper, we propose a novel machine learning criterion that can terminate a streaming neutron tomography scan once sufficient information is obtained based on the current set of measurements. Our decision criterion uses a quality score which combines a reference-free image quality metric computed using a pre-trained deep neural network with a metric that measures differences between consecutive reconstructions. The results show that our method can reduce the measurement time by approximately a factor of five compared to a baseline method based on filtered back projection for the samples we studied while automatically terminating the scans.

Cancer screening research in Bangladesh: Insights from a scoping review.

This scoping review summarises the findings of research conducted on cancer screening in Bangladesh, including the prevalence, awareness, barriers, and evaluation of screening programmes, by performing a comprehensive search of electronic databases and gray literature. 25 studies that met inclusion criteria were included in the final analysis. Most of the studies were about screening for cervical cancer, were quantitative, were cross-sectional, and were conducted in hospital settings. The main challenges to screening uptake were shyness, fear, a lack of knowledge, and an inadequate understanding of the concept of screening. Visual inspection with acetic acid (VIA) was found to be a simple and cost-efficient way to detect early-stage cervical cancer. However, breast self-examination (BSE) was reported to be insufficient. Education was found to have a positive impact on cancer screening knowledge and practice, but more needs to be done to improve screening rates, such as the utilisation of media, particularly in rural areas. The results of this scoping review highlight Bangladesh's low cancer screening prevalence and uptake and suggest that targeted awareness campaigns and enhanced access to screening services are required to increase cancer screening uptake and reduce the cancer burden in Bangladesh.

Amplification- and Enzyme-Free Magnetic Diagnostics Circuit for Whole-Genome Detection of SARS-CoV-2 RNA.

Polymerase chain reaction (PCR) requires thermal cycling and enzymatic reactions for sequence amplification, hampering their applications in point-of-care (POC) settings. Magnetic bioassays based on magnetic particle spectroscopy (MPS) and magnetic nanoparticles (MNPs) are isothermal, wash-free, and can be quantitative. Realizing them amplification- and enzyme-free on a benchtop device, they will become irreplaceable for POC applications. Here we demonstrate a first-in-class magnetic signal amplification circuit (MAC) that enables detection of whole genome of SARS-CoV-2 by combining the specificity of toehold-mediated DNA strand displacement with the magnetic response of MNPs to declustering processes. Using MAC, we detect the N gene of SARS-CoV-2 samples at a concentration of 104 RNA copies/µl as determined by droplet digital PCR. Further, we demonstrate that MAC can reliably distinguish between SARS-CoV-2 and other human coronaviruses. Being a wash-, amplification- and enzyme-free biosensing concept and working at isothermal conditions (25 °C) on a low-cost benchtop MPS device, our MAC biosensing concept offers several indispensable features for translating nucleic acid detection to POC applications.

Determinants of low birth weight and its effect on childhood health and nutritional outcomes in Bangladesh.

BACKGROUND: The high incidence of low birth weight (LBW) is associated with an increased risk of infant mortality, adverse pregnancy outcomes for mothers, and a decline in overall health and well-being. The current study aimed to identify the various determinants of LBW and its effect on adverse health and nutritional outcomes of children aged 0-23 months in Bangladesh. METHODS: Bangladesh Demography and Health Survey (BDHS) 2017-18 data was used. A chi-square test and multivariable logistic regression analysis were used to find out the associations between independent variables and outcomes (e.g., LBW, child illness and undernutrition). RESULTS: The overall prevalence of LBW among was 16.3%. Mother with no formal education (AOR = 2.64, 95% CI = 0.55-3.30, p = 0.01), female child (AOR = 1.31, 95% CI = 1.04-1.65, p = 0.023); and poorest economic status (AOR = 1.69, 95% CI = 1.13-2.51, p = 0.010), were identified significant determinants of LBW. Of home environment and hygiene factors, unimproved toilet facilities (AOR = 1.38, 95% CI = 1.03-1.84, p = 0.030) had a significant effect on LBW. In addition, children born with LBW were more likely to suffer fever (AOR = 1.26, 95% CI = 1.05-1.60, p = 0.050), stunting (AOR = 2.42, 95% CI = 1.86-3.15, p = < 0.001), wasting (AOR = 1.47, 95% CI = 1.02-2.25 p = 0.049), and underweight (AOR = 3.19, 95% CI = 2.40-4.23, p = < 0.001). CONCLUSION: One out of five children was LBW in Bangladesh. Maternal education, sex of child, wealth index, and toilet facilities had significant effects on LBW. In addition, LWB contributed to children's poor health and nutritional outcomes. Enhancing maternal pregnancy, and child health outcomes necessitates policies addressing poverty, gender inequality, and social disparities. Key strategies include promoting regular prenatal care, early medical intervention, reproductive health education, and safe hygiene practices. To combat the negative impacts of LBW, a comprehensive strategy is vital, encompassing exclusive breastfeeding, nutritional support, growth monitoring, accessible healthcare, and caregiver education.

Combining species distribution models and big datasets may provide finer assessments of snakebite impacts.

BACKGROUND: Snakebite is a major poverty-related neglected tropical disease. An integrated scientific approach is needed to understand the dynamics of this important health issue. Our objective was to estimate snakebite occurrence in a tropical area by using a blend of ecological modelling and robust statistical analysis. METHODS: The present study used climatic, environmental, and human population density data to determine the area with snakebite occurrence-probability for the first time in Bangladesh. We also analysed a large, 16-year dataset of hospitalized snakebite cases to reveal the epidemiology of snakebite in the south-eastern zone of the country. FINDINGS: Our results show that cobra bite is the most commonly occurring venomous snakebite in humans (around ~12% of the total yearly snakebite records), and men are more frequently bitten than women (2/3 of human victims are men). Most bites occur during the rainy season for cobra and green pit viper, while krait bites are not restricted to any particular season. As snakebite incidents are closely related to climate conditions, we can model snakebite risk using temperature and precipitation variables. Whereas there is a lack of snakebite reports from several parts of the study area in official records, our models predict that the entire study area is favourable for snakebite incidents. Based on the combined evidence we estimate that about 200,000 snakebite events occur every year in the south-eastern part of Bangladesh alone. Considering future global climate change, our model projections show that snakebite incidence in Bangladesh might not significantly decrease in the future (- 2070-); however, the distribution of probabilities might change, with a predicted increase of snakebite incidence in the hilly areas of the country. CONCLUSIONS: Using climatic data to predict snakebite incidence in Bangladesh allowed us to provide estimations of the total annual number of snakebite cases in the study area. As in most countries, the scarcity of accurate epidemiological data in official records might have masked the real magnitude of this problem. Our analysis suggests that the problem of snakebite envenoming in Bangladesh might be worse than currently perceived. A long-term sustainable snakebite program plan should be designed and institutionalized, considering climatic, geographical and human demographic variables, to obtain better data and facilitate the implementation of accurate snakebite management programs for this country.

Superior Induced Pluripotent Stem Cell Generation through Phactr3-Driven Mechanomodulation of Both Early and Late Phases of Cell Reprogramming.

Human cell reprogramming traditionally involves time-intensive, multistage, costly tissue culture polystyrene-based cell culture practices that ultimately produce low numbers of reprogrammed cells of variable quality. Previous studies have shown that very soft 2- and 3-dimensional hydrogel substrates/matrices (of stiffnesses ≤ 1 kPa) can drive ~2× improvements in human cell reprogramming outcomes. Unfortunately, these similarly complex multistage protocols lack intrinsic scalability, and, furthermore, the associated underlying molecular mechanisms remain to be fully elucidated, limiting the potential to further maximize reprogramming outcomes. In screening the largest range of polyacrylamide (pAAm) hydrogels of varying stiffness to date (1 kPa to 1.3 MPa), we have found that a medium stiffness gel (~100 kPa) increased the overall number of reprogrammed cells by up to 10-fold (10×), accelerated reprogramming kinetics, improved both early and late phases of reprogramming, and produced induced pluripotent stem cells (iPSCs) having more naïve characteristics and lower remnant transgene expression, compared to the gold standard tissue culture polystyrene practice. Functionalization of these pAAm hydrogels with poly-l-dopamine enabled, for the first-time, continuous, single-step reprogramming of fibroblasts to iPSCs on hydrogel substrates (noting that even the tissue culture polystyrene practice is a 2-stage process). Comparative RNA sequencing analyses coupled with experimental validation revealed that a novel reprogramming regulator, protein phosphatase and actin regulator 3, up-regulated under the gel condition at a very early time point, was responsible for the observed enhanced reprogramming outcomes. This study provides a novel culture protocol and substrate for continuous hydrogel-based cell reprogramming and previously unattained clarity of the underlying mechanisms via which substrate stiffness modulates reprogramming kinetics and iPSC quality outcomes.

Guideline Recommendations on Behavioral and Psychological Symptoms of Dementia: A Systematic Review.

OBJECTIVE: To synthesize recommendations on assessing and managing behavioral and psychological symptoms of dementia (BPSDs) in existing clinical practice guidelines on dementia care to learn from and adapt recommendations to a Canadian context and language for describing BPSDs. DESIGN: Systematic review. SETTING AND PARTICIPANTS: Moderate to high-quality clinical practice guidelines on dementia care that made 1 or more recommendations on BPSD assessment or management. METHODS: We searched MEDLINE, Embase, JBI EBM, PsycINFO, AgeLine, and gray literature for clinical practice guidelines on dementia care making recommendations on BPSD, published between January 1, 2011, and October 13, 2022. Two independent reviewers conducted study screening and data abstraction. Four independent reviewers completed quality appraisal using the Appraisal of Guidelines for Research and Evaluation (AGREE) II tool; included guidelines had a mean overall AGREE II score ≥4. RESULTS: Our systematic review identified 23 moderate to high-quality clinical practice guidelines (264 recommendations). The mean overall quality score on the AGREE II tool ranged from 4 to 6.5. Recommendations were clearly presented (mean clarity of presentation score 73.5%), but guideline applicability was not consistently addressed (mean applicability score 39.3%). BPSD was the most prevalent term describing neuropsychiatric symptoms (number of guidelines [n] = 14). People with lived experience contributed to 6 guidelines (26.1%). Ten guidelines (43.5%) described 1 or more health equity considerations. Guidelines made recommendations for assessing and managing agitation (n = 12), aggression (n = 10), psychosis (n = 11), depression (n = 9), anxiety (n = 5), apathy (n = 6), inappropriate sexual behavior (n = 3), nighttime behavior (n = 5), and eating disturbances (n = 3). There was substantial variability in recommendation statements, evidence quality assigned to each statement, and strength of recommendations. CONCLUSIONS AND IMPLICATIONS: There are several moderate to high-quality clinical practice guidelines making recommendations on BPSD assessment and management, but variability in recommendation statements across guidelines and insufficient consideration of guideline applicability may hamper guideline dissemination and implementation in clinical practice.

Preoperative Variables of 30-Day Mortality in Adults Undergoing Percutaneous Coronary Intervention: A Systematic Review.

BACKGROUND AND AIM: Risk adjustment following percutaneous coronary intervention (PCI) is vital for clinical quality registries, performance monitoring, and clinical decision-making. There remains significant variation in the accuracy and nature of risk adjustment models utilised in international PCI registries/databases. Therefore, the current systematic review aims to summarise preoperative variables associated with 30-day mortality among patients undergoing PCI, and the other methodologies used in risk adjustments. METHOD: The MEDLINE, EMBASE, CINAHL, and Web of Science databases until October 2022 without any language restriction were systematically searched to identify preoperative independent variables related to 30-day mortality following PCI. Information was systematically summarised in a descriptive manner following the Checklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies checklist. The quality and risk of bias of all included articles were assessed using the Prediction Model Risk Of Bias Assessment Tool. Two independent investigators took part in screening and quality assessment. RESULTS: The search yielded 2,941 studies, of which 42 articles were included in the final assessment. Logistic regression, Cox-proportional hazard model, and machine learning were utilised by 27 (64.3%), 14 (33.3%), and one (2.4%) article, respectively. A total of 74 independent preoperative variables were identified that were significantly associated with 30-day mortality following PCI. Variables that repeatedly used in various models were, but not limited to, age (n=36, 85.7%), renal disease (n=29, 69.0%), diabetes mellitus (n=17, 40.5%), cardiogenic shock (n=14, 33.3%), gender (n=14, 33.3%), ejection fraction (n=13, 30.9%), acute coronary syndrome (n=12, 28.6%), and heart failure (n=10, 23.8%). Nine (9; 21.4%) studies used missing values imputation, and 15 (35.7%) articles reported the model's performance (discrimination) with values ranging from 0.501 (95% confidence interval [CI] 0.472-0.530) to 0.928 (95% CI 0.900-0.956), and four studies (9.5%) validated the model on external/out-of-sample data. CONCLUSIONS: Risk adjustment models need further improvement in their quality through the inclusion of a parsimonious set of clinically relevant variables, appropriately handling missing values and model validation, and utilising machine learning methods.

Ethical and Equitable Digital Health Research: Ensuring Self-Determination in Data Governance for Racialized Communities.

Recent studies highlight the need for ethical and equitable digital health research that protects the rights and interests of racialized communities. We argue for practices in digital health that promote data self-determination for these communities, especially in data collection and management. We suggest that researchers partner with racialized communities to curate data that reflects their wellness understandings and health priorities, and respects their consent over data use for policy and other outcomes. These data governance approach honors and builds on Indigenous Data Sovereignty (IDS) decolonial scholarship by Indigenous and non-indigenous researchers and its adaptations to health research involving racialized communities from former European colonies in the global South. We discuss strategies to practice equity, diversity, inclusion, accessibility and decolonization (EDIAD) principles in digital health. We draw upon and adapt the concept of Precision Health Equity (PHE) to emphasize models of data sharing that are co-defined by racialized communities and researchers, and stress their shared governance and stewardship of data that is generated from digital health research. This paper contributes to an emerging research on equity issues in digital health and reducing health, institutional, and technological disparities. It also promotes the self-determination of racialized peoples through ethical data management.

Creation of a boron carbide-based Ti3AlBC (312) MAX phase: a route to novel MXenes for energy storage.

A novel boron carbide (B4C)-based Ti3AlBC (312) MAX phase was predicted for the first time via density functional theory (DFT). The stability of the MAX phase was confirmed by mechanical and thermal property analyses. The computational details revealed the attractive properties of Ti3AlBC, indicating its potential as an advanced material with improved characteristics. Its thermodynamic properties are reported as a function of temperature, indicating its potential for energy storage applications.

Automatic Segmentation of Bone Marrow Lesions on MRI Using a Deep Learning Method.

Bone marrow lesion (BML) volume is a potential biomarker of knee osteoarthritis (KOA) as it is associated with cartilage degeneration and pain. However, segmenting and quantifying the BML volume is challenging due to the small size, low contrast, and various positions where the BML may occur. It is also time-consuming to delineate BMLs manually. In this paper, we proposed a fully automatic segmentation method for BMLs without requiring human intervention. The model takes intermediate weighted fat-suppressed (IWFS) magnetic resonance (MR) images as input, and the output BML masks are evaluated using both regular 2D Dice similarity coefficient (DSC) of the slice-level area metric and 3D DSC of the subject-level volume metric. On a dataset with 300 subjects, each subject has a sequence of 36 IWFS MR images approximately. We randomly separated the dataset into training, validation, and testing sets with a 70%/15%/15% split at the subject level. Since not every subject or image has a BML, we excluded the images without a BML in each subset. The ground truth of the BML was labeled by trained medical staff using a semi-automatic tool. Compared with the ground truth, the proposed segmentation method achieved a Pearson's correlation coefficient of 0.98 between the manually measured volumes and automatically segmented volumes, a 2D DSC of 0.68, and a 3D DSC of 0.60 on the testing set. Although the DSC result is not high, the high correlation of 0.98 indicates that the automatically measured BML volume is strongly correlated with the manually measured BML volume, which shows the potential to use the proposed method as an automatic measurement tool for the BML biomarker to facilitate the assessment of knee OA progression.

Fast Track versus Conventional Perioperative Care Protocols in Paediatric Intestinal Stoma Closure ‒ A Randomised Study.

BACKGROUND: It is still unclear to what extent fast-track (FT) surgery is applicable in paediatric surgery. The aim of the study was to compare the outcome between FT and conventional perioperative care protocols in paediatric intestinal stoma closure to assess the safety for future application. MATERIALS AND METHODS: This study was a prospective randomised study. Twenty-six paediatric patients who underwent intestinal stoma closure from December 2019 to March 2021 were divided into two groups: group A, conventional methods and Group B FT protocol. The FT protocol included minimal pre-operative fasting, no pre-operative bowel preparation, no routine intraoperative use of nasogastric tube, drain tube, urinary catheter, early post-operative enteral feeding, early mobilisation, non-opioid analgesics and prophylactic use of anti-emetic. Total length of post-operative hospital stays and complications between these two groups were compared. RESULTS: No significant differences were found between the two groups regarding anastomotic leak (nil in both groups), wound infection (7.7% in Group A vs. 0% in Group B; P = 1.0) and wound dehiscence (7.7% in Group A vs. 0% in Group B; P = 1.0). No significant differences were found in post-operative length of stay (median 5, interquartile range [IQR] 4-9 in Group A and median 6, IQR 4-7 in Group B, P = 0.549) and time to appearance of bowel function (passage of stool) (median 2 days in both groups; P = 0.978). CONCLUSIONS: FT surgery was comparable to the conventional method in terms of complication and thus can reduce unnecessary interventions.

Cooperative dynamics of DNA-grafted magnetic nanoparticles optimize magnetic biosensing and coupling to DNA origami.

Magnetic nanoparticles (MNPs) provide new opportunities for enzyme-free biosensing of nucleic acid biomarkers and magnetic actuation by patterning on DNA origami, yet how the DNA grafting density affects their dynamics and accessibility remains poorly understood. Here, we performed surface functionalization of MNPs with single-stranded DNA (ssDNA) via click chemistry with a tunable grafting density, which enables the encapsulation of single MNPs inside a functional polymeric layer. We used several complementary methods to show that particle translational and rotational dynamics exhibit a sigmoidal dependence on the ssDNA grafting density. At low densities, ssDNA strands adopt a coiled conformation that results in minor alterations to particle dynamics, while at high densities, they organize into polymer brushes that collectively influence particle dynamics. Intermediate ssDNA densities, where the dynamics are most sensitive to changes, show the highest magnetic biosensing sensitivity for the detection of target nucleic acids. Finally, we demonstrate that MNPs with high ssDNA grafting densities are required to efficiently couple to DNA origami. Our results establish ssDNA grafting density as a critical parameter for the functionalization of MNPs for magnetic biosensing and functionalization of DNA nanostructures.

Feedback control of automatic navigation for cyborg cockroach without external motion capture system.

Due to their size and locomotion ability, cockroaches are favorable as hybrid robot platforms in search and rescue (SAR) missions. However, cockroaches most likely approach the corner area and stay for an uncertain time. This natural behavior will hinder the utilization of cyborg cockroaches in SAR missions under rubble, unstructured, and unknown areas. Therefore, we proposed onboard automatic obstacle avoidance and human detection that can run on the wireless backpack stimulator without an external motion capture system. A low-power and small-size Time of Flight (ToF) sensor was selected as a distance measurement sensor, while a low-resolution thermopile array sensor was applied for human presence detection. The implemented feedback control based on IMU and ToF sensors has successfully navigated the cyborg cockroach to avoid obstacles and escape from the sharp corners in the laboratory unstructured area without stopping or being trapped. It could also recognize the human presence when the human was in front of it in real-time. Due to its performance, the random forest classifier was implemented as an embedded human detection system. It could achieve the highest accuracy at a distance of around 25 cm (92.5%) and the lowest accuracy at about 100 cm (70%).

Leveraging deep neural networks to uncover unprecedented levels of precision in the diagnosis of hair and scalp disorders.

BACKGROUND: Hair and scalp disorders present a significant challenge in dermatology due to their clinical diversity and overlapping symptoms, often leading to misdiagnoses. Traditional diagnostic methods rely heavily on clinical expertise and are limited by subjectivity and accessibility, necessitating more advanced and accessible diagnostic tools. Artificial intelligence (AI) and deep learning offer a promising solution for more accurate and efficient diagnosis. METHODS: The research employs a modified Xception model incorporating ReLU activation, dense layers, global average pooling, regularization and dropout layers. This deep learning approach is evaluated against existing models like VGG19, Inception, ResNet, and DenseNet for its efficacy in accurately diagnosing various hair and scalp disorders. RESULTS: The model achieved a 92% accuracy rate, significantly outperforming the comparative models, with accuracies ranging from 50% to 80%. Explainable AI techniques like Gradient-weighted Class Activation Mapping (Grad-CAM) and Saliency Map provided deeper insights into the model's decision-making process. CONCLUSION: This study emphasizes the potential of AI in dermatology, particularly in accurately diagnosing hair and scalp disorders. The superior accuracy and interpretability of the model represents a significant advancement in dermatological diagnostics, promising more reliable and accessible diagnostic methods.

Blockchain of Things: Benefits, Challenges and Future Directions.

As Internet of Things (IoT) technologies become increasingly integrated into our daily lives through a multitude of Internet-enabled devices, the efficient, secure, and cost-effective management of the vast amount of data generated by these devices poses a significant challenge [...].

Green finance and environmental sustainability: a systematic review and future research avenues.

This study critically examines the dynamic interplay between green finance and environmental sustainability using a systematic review and bibliometric analysis. The analysis is centered on 507 scholarly articles published between 2013 and 2023 in the Scopus database and leverages Microsoft Excel, Harzing Publish or Perish, and VOSviewer to identify publication trends, key contributors, research impact, and emergent themes in this rapidly evolving field. The findings reveal that research on green finance and environmental sustainability has increased exponentially over the past decade, with China and institutions in Asia emerging as prominent contributors compared to other regions. This study also identified the Environmental Science and Pollution Research journal as the most active source title, demonstrating its commitment to publishing current findings on the topic. Through keyword analysis, several research avenues have been proposed to guide future research on enhancing the strategic role of green finance in promoting environmental sustainability. These avenues include broadening the geographical scope of research, exploring the synergies between green finance and emerging fintech innovations, developing robust metrics to quantify the socioeconomic impacts of green finance, establishing a risk and resilience framework to protect green finance against uncertainties, and creating a Green Finance Performance Index to evaluate the dual returns of environmental and financial performance.

The Tumor Suppressor SOCS1 Diminishes Tolerance to Oxidative Stress in Hepatocellular Carcinoma.

SOCS1 is a tumor suppressor in hepatocellular carcinoma (HCC). Recently, we showed that a loss of SOCS1 in hepatocytes promotes NRF2 activation. Here, we investigated how SOCS1 expression in HCC cells affected oxidative stress response and modulated the cellular proteome. Murine Hepa1-6 cells expressing SOCS1 (Hepa-SOCS1) or control vector (Hepa-Vector) were treated with cisplatin or tert-butyl hydroperoxide (t-BHP). The induction of NRF2 and its target genes, oxidative stress, lipid peroxidation, cell survival and cellular proteome profiles were evaluated. NRF2 induction was significantly reduced in Hepa-SOCS1 cells. The gene and protein expression of NRF2 targets were differentially induced in Hepa-Vector cells but markedly suppressed in Hepa-SOCS1 cells. Hepa-SOCS1 cells displayed an increased induction of reactive oxygen species but reduced lipid peroxidation. Nonetheless, Hepa-SOCS1 cells treated with cisplatin or t-BHP showed reduced survival. GCLC, poorly induced in Hepa-SOCS1 cells, showed a strong positive correlation with NFE2L2 and an inverse correlation with SOCS1 in the TCGA-LIHC transcriptomic data. A proteomic analysis of Hepa-Vector and Hepa-SOCS1 cells revealed that SOCS1 differentially modulated many proteins involved in diverse molecular pathways, including mitochondrial ROS generation and ROS detoxification, through peroxiredoxin and thioredoxin systems. Our findings indicate that maintaining sensitivity to oxidative stress is an important tumor suppression mechanism of SOCS1 in HCC.

Involuntary delayed retirement and mental health of older adults.

OBJECTIVE: This study examined the association of multiple mental health measures with involuntary delayed retirement (IDR) in working older adults (≥ 65 years) in the USA. METHODS: Data were derived from the Health and Retirement Study, focusing on two combined waves of working older adults in 2010 and 2012. IDR was measured as the desire to stop working but the inability to do so due to financial constraints. In addition, mental health outcomes included depression, anxiety, anger-in, and anger-out. Using Stata 16.0, primary analyses were conducted for descriptive statistics and multivariable logistic regression. The odds ratios were reported with 95% confidence intervals (CIs). RESULTS: Older adults who reported IDR were more likely to have depression (OR = 3.20, CI = 1.03-9.88), anxiety (OR = 2.12, CI = 1.00-5.18), and anger-in (OR = 1.71, CI = 1.12-2.60) compared to those who did not report IDR. However, IDR was not significantly associated with anger-out in older adults who worked past the traditional retirement age. CONCLUSION: The findings suggest that IDR is likely to act as a stressor and affects the mental health of older adults aged 65 and more. Policymakers should pay more attention to helping older adults maintain positive mental health even if they are required to work past retirement age.

Effect of thermal shock and sustained heat treatment on mainstream partial nitrification and microbial community in sequencing batch reactors.

In order to develop a promising means of achieving mainstream short-cut nitrification, this study evaluated the effect of thermal shock on nitrite accumulation using intermittent offline and continuous inline heat treatment of biomass in sequencing batch reactors (SBRs). The SBRs fed with municipal wastewater were operated at a solid retention time of 7 days and nitrogen loading rate of 0.04 gN/L·d to 0.08 gN/L·d without the application of pre-treatment. Contrary to literature studies that showed suppression of nitrite-oxidizing bacteria at temperature 60 to 80 °C, nitrite accumulation was achieved temporarily when 20% of the biomass was heated for 2 h at 47 °C, as well as in continuously heated SBRs at 37 °C and 42 °C. The continuously heated reactors at 37 °C and 42 °C produced a maximum nitrite accumulation ratio (NAR) of 0.59 and 0.79, respectively, whereas the intermittent offline heating at 47 °C-2 h produced a NAR of 0.37. Although nitrite accumulation was stable only for 10-12 days in all heated reactors, this study demonstrates the achievement of mainstream partial nitrification (PN) at lower temperature (42 °C) than that reported in literature and also highlights the potential for achieving PN by implementing heat treatment of a portion of the return activated sludge (RAS) in biological nitrogen removal (BNR) systems. During the time when full nitrification was achieved, Nitrospira was more dominant than Nitrosomonas in all reactors at ratios of 1.4:1, 2.4:1, 2.4:1, and 3.7:1 for the control SBR (22 °C), 47 °C -2 h offline heating SBR, 37 °C SBR, and 42 °C SBR, respectively, suggesting that it may have played a role as a comammox bacteria capable of degrading ammonia to nitrates at elevated temperature.