Impact of Asian and Black Donor and Recipient Ethnicity on the Outcomes After Deceased Donor Kidney Transplantation in the United Kingdom.

Patients of Asian and black ethnicity face disadvantage on the renal transplant waiting list in the UK, because of lack of human leucocyte antigen and blood group matched donors from an overwhelmingly white deceased donor pool. This study evaluates outcomes of renal allografts from Asian and black donors. The UK Transplant Registry was analysed for adult deceased donor kidney only transplants performed between 2001 and 2015. Asian and black ethnicity patients constituted 12.4% and 6.7% of all deceased donor recipients but only 1.6% and 1.2% of all deceased donors, respectively. Unadjusted survival analysis demonstrated significantly inferior long-term allograft outcomes associated with Asian and black donors, compared to white donors. On Cox-regression analysis, Asian donor and black recipient ethnicities were associated with poorer outcomes than white counterparts, and on ethnicity matching, compared with the white donor-white recipient baseline group and adjusting for other donor and recipient factors, 5-year graft outcomes were significantly poorer for black donor-black recipient, Asian donor-white recipient, and white donor-black recipient combinations in decreasing order of worse unadjusted 5-year graft survival. Increased deceased donation among ethnic minorities could benefit the recipient pool by increasing available organs. However, it may require a refined approach to enhance outcomes.

A smoking cessation smartphone app that delivers real-time 'context aware' behavioural support: the Quit Sense feasibility RCT.

Background: During a quit attempt, cues from a smoker's environment are a major cause of brief smoking lapses, which increase the risk of relapse. Quit Sense is a theory-guided Just-In-Time Adaptive Intervention smartphone app, providing smokers with the means to learn about their environmental smoking cues and provides 'in the moment' support to help them manage these during a quit attempt. Objective: To undertake a feasibility randomised controlled trial to estimate key parameters to inform a definitive randomised controlled trial of Quit Sense. Design: A parallel, two-arm randomised controlled trial with a qualitative process evaluation and a 'Study Within A Trial' evaluating incentives on attrition. The research team were blind to allocation except for the study statistician, database developers and lead researcher. Participants were not blind to allocation. Setting: Online with recruitment, enrolment, randomisation and data collection (excluding manual telephone follow-up) automated through the study website. Participants: Smokers (323 screened, 297 eligible, 209 enrolled) recruited via online adverts on Google search, Facebook and Instagram. Interventions: Participants were allocated to 'usual care' arm (n = 105; text message referral to the National Health Service SmokeFree website) or 'usual care' plus Quit Sense (n = 104), via a text message invitation to install the Quit Sense app. Main outcome measures: Follow-up at 6 weeks and 6 months post enrolment was undertaken by automated text messages with an online questionnaire link and, for non-responders, by telephone. Definitive trial progression criteria were met if a priori thresholds were included in or lower than the 95% confidence interval of the estimate. Measures included health economic and outcome data completion rates (progression criterion #1 threshold: ≥ 70%), including biochemical validation rates (progression criterion #2 threshold: ≥ 70%), recruitment costs, app installation (progression criterion #3 threshold: ≥ 70%) and engagement rates (progression criterion #4 threshold: ≥ 60%), biochemically verified 6-month abstinence and hypothesised mechanisms of action and participant views of the app (qualitative). Results: Self-reported smoking outcome completion rates were 77% (95% confidence interval 71% to 82%) and health economic data (resource use and quality of life) 70% (95% CI 64% to 77%) at 6 months. Return rate of viable saliva samples for abstinence verification was 39% (95% CI 24% to 54%). The per-participant recruitment cost was £19.20, which included advert (£5.82) and running costs (£13.38). In the Quit Sense arm, 75% (95% CI 67% to 83%; 78/104) installed the app and, of these, 100% set a quit date within the app and 51% engaged with it for more than 1 week. The rate of 6-month biochemically verified sustained abstinence, which we anticipated would be used as a primary outcome in a future study, was 11.5% (12/104) in the Quit Sense arm and 2.9% (3/105) in the usual care arm (estimated effect size: adjusted odds ratio = 4.57, 95% CIs 1.23 to 16.94). There was no evidence of between-arm differences in hypothesised mechanisms of action. Three out of four progression criteria were met. The Study Within A Trial analysis found a £20 versus £10 incentive did not significantly increase follow-up rates though reduced the need for manual follow-up and increased response speed. The process evaluation identified several potential pathways to abstinence for Quit Sense, factors which led to disengagement with the app, and app improvement suggestions. Limitations: Biochemical validation rates were lower than anticipated and imbalanced between arms. COVID-19-related restrictions likely limited opportunities for Quit Sense to provide location tailored support. Conclusions: The trial design and procedures demonstrated feasibility and evidence was generated supporting the efficacy potential of Quit Sense. Future work: Progression to a definitive trial is warranted providing improved biochemical validation rates. Trial registration: This trial is registered as ISRCTN12326962. Funding: This award was funded by the National Institute for Health and Care Research (NIHR) Public Health Research programme (NIHR award ref: 17/92/31) and is published in full in Public Health Research; Vol. 12, No. 4. See the NIHR Funding and Awards website for further award information.

Smokers often fail to quit because of urges to smoke triggered by their surroundings (e.g. being around smokers). We developed a smartphone app ('Quit Sense') which learns about an individual's surroundings and locations where they smoke. During a quit attempt, Quit Sense uses in-built sensors to identify when smokers are in those locations and sends 'in the moment' advice to help prevent them from smoking. We ran a feasibility study to help plan for a future large study to see if Quit Sense helps smokers to quit. This feasibility study was designed to tell us how many participants complete study measures; recruitment costs; how many participants install and use Quit Sense; and estimate whether Quit Sense may help smokers to stop and how it might do this. We recruited 209 smokers using online adverts on Google search, Facebook and Instagram, costing £19 per participant. Participants then had an equal chance of receiving a web link to the National Health Service SmokeFree website ('usual care group') or receive that same web link plus a link to the Quit Sense app ('Quit Sense group'). Three-quarters of the Quit Sense group installed the app on their phone and half of these used the app for more than 1 week. We followed up 77% of participants at 6 months to collect study data, though only 39% of quitters returned a saliva sample for abstinence verification. At 6 months, more people in the Quit Sense group had stopped smoking (12%) than the usual care group (3%). It was not clear how the app helped smokers to quit based on study measures, though interviews found that the process of training the app helped people quit through learning about what triggered their smoking behaviour. The findings support undertaking a large study to tell us whether Quit Sense really does help smokers to quit.

Acute Cardiac Events in Hospitalized Older Adults With Respiratory Syncytial Virus Infection.

Importance: Respiratory syncytial virus (RSV) infection can cause severe respiratory illness in older adults. Less is known about the cardiac complications of RSV disease compared with those of influenza and SARS-CoV-2 infection. Objective: To describe the prevalence and severity of acute cardiac events during hospitalizations among adults aged 50 years or older with RSV infection. Design, Setting, and Participants: This cross-sectional study analyzed surveillance data from the RSV Hospitalization Surveillance Network, which conducts detailed medical record abstraction among hospitalized patients with RSV infection detected through clinician-directed laboratory testing. Cases of RSV infection in adults aged 50 years or older within 12 states over 5 RSV seasons (annually from 2014-2015 through 2017-2018 and 2022-2023) were examined to estimate the weighted period prevalence and 95% CIs of acute cardiac events. Exposures: Acute cardiac events, identified by International Classification of Diseases, 9th Revision, Clinical Modification or International Statistical Classification of Diseases, Tenth Revision, Clinical Modification discharge codes, and discharge summary review. Main Outcomes and Measures: Severe disease outcomes, including intensive care unit (ICU) admission, receipt of invasive mechanical ventilation, or in-hospital death. Adjusted risk ratios (ARR) were calculated to compare severe outcomes among patients with and without acute cardiac events. Results: The study included 6248 hospitalized adults (median [IQR] age, 72.7 [63.0-82.3] years; 59.6% female; 56.4% with underlying cardiovascular disease) with laboratory-confirmed RSV infection. The weighted estimated prevalence of experiencing a cardiac event was 22.4% (95% CI, 21.0%-23.7%). The weighted estimated prevalence was 15.8% (95% CI, 14.6%-17.0%) for acute heart failure, 7.5% (95% CI, 6.8%-8.3%) for acute ischemic heart disease, 1.3% (95% CI, 1.0%-1.7%) for hypertensive crisis, 1.1% (95% CI, 0.8%-1.4%) for ventricular tachycardia, and 0.6% (95% CI, 0.4%-0.8%) for cardiogenic shock. Adults with underlying cardiovascular disease had a greater risk of experiencing an acute cardiac event relative to those who did not (33.0% vs 8.5%; ARR, 3.51; 95% CI, 2.85-4.32). Among all hospitalized adults with RSV infection, 18.6% required ICU admission and 4.9% died during hospitalization. Compared with patients without an acute cardiac event, those who experienced an acute cardiac event had a greater risk of ICU admission (25.8% vs 16.5%; ARR, 1.54; 95% CI, 1.23-1.93) and in-hospital death (8.1% vs 4.0%; ARR, 1.77; 95% CI, 1.36-2.31). Conclusions and Relevance: In this cross-sectional study over 5 RSV seasons, nearly one-quarter of hospitalized adults aged 50 years or older with RSV infection experienced an acute cardiac event (most frequently acute heart failure), including 1 in 12 adults (8.5%) with no documented underlying cardiovascular disease. The risk of severe outcomes was nearly twice as high in patients with acute cardiac events compared with patients who did not experience an acute cardiac event. These findings clarify the baseline epidemiology of potential cardiac complications of RSV infection prior to RSV vaccine availability.

Characteristics and Outcomes of Pregnant Women Hospitalized With Laboratory-Confirmed Respiratory Syncytial Virus Before and During the COVID-19 Pandemic.

Background: Respiratory syncytial virus (RSV) can cause severe disease among infants and older adults. Less is known about RSV among pregnant women. Methods: To analyze hospitalizations with laboratory-confirmed RSV among women aged 18 to 49 years, we used data from the RSV Hospitalization Surveillance Network (RSV-NET), a multistate population-based surveillance system. Specifically, we compared characteristics and outcomes among (1) pregnant and nonpregnant women during the pre-COVID-19 pandemic period (2014-2018), (2) pregnant women with respiratory symptoms during the prepandemic and pandemic periods (2021-2023), and (3) pregnant women with and without respiratory symptoms in the pandemic period. Using multivariable logistic regression, we examined whether pregnancy was a risk factor for severe outcomes (intensive care unit admission or in-hospital death) among women aged 18 to 49 years who were hospitalized with RSV prepandemic. Results: Prepandemic, 387 women aged 18 to 49 years were hospitalized with RSV. Of those, 350 (90.4%) had respiratory symptoms, among whom 33 (9.4%) were pregnant. Five (15.2%) pregnant women and 74 (23.3%) nonpregnant women were admitted to the intensive care unit; no pregnant women and 5 (1.6%) nonpregnant women died. Among 279 hospitalized pregnant women, 41 were identified prepandemic and 238 during the pandemic: 80.5% and 35.3% had respiratory symptoms, respectively (P < .001). Pregnant women were more likely to deliver during their RSV-associated hospitalization during the pandemic vs the prepandemic period (73.1% vs 43.9%, P < .001). Conclusions: Few pregnant women had severe RSV disease, and pregnancy was not a risk factor for a severe outcome. More asymptomatic pregnant women were identified during the pandemic, likely due to changes in testing practices for RSV.

Potential of APSIS-InSAR for measuring surface oscillations of tropical peatlands.

Tropical peatland across Southeast Asia is drained extensively for production of pulpwood, palm oil and other food crops. Associated increases in peat decomposition have led to widespread subsidence, deterioration of peat condition and CO2 emissions. However, quantification of subsidence and peat condition from these processes is challenging due to the scale and inaccessibility of dense tropical peat swamp forests. The development of satellite interferometric synthetic aperture radar (InSAR) has the potential to solve this problem. The Advanced Pixel System using Intermittent Baseline Subset (APSIS, formerly ISBAS) modelling technique provides improved coverage across almost all land surfaces irrespective of ground cover, enabling derivation of a time series of tropical peatland surface oscillations across whole catchments. This study aimed to establish the extent to which APSIS-InSAR can monitor seasonal patterns of tropical peat surface oscillations at North Selangor Peat Swamp Forest, Peninsular Malaysia. Results showed that C-band SAR could penetrate the forest canopy over tropical peat swamp forests intermittently and was applicable to a range of land covers. Therefore the APSIS technique has the potential for monitoring peat surface oscillations under tropical forest canopy using regularly acquired C-band Sentinel-1 InSAR data, enabling continuous monitoring of tropical peatland surface motion at a spatial resolution of 20 m.

Meta-analysis of macrophage nanoparticle targeting across blood and solid tumors using an eLDA Topic modeling Machine Learning approach.

The role of macrophages in regulating the tumor microenvironment has spurned the exponential generation of nanoparticle targeting technologies. With the large amount of literature and the speed at which it is generated it is difficult to remain current with the most up-to-date literature. In this study we performed a topic modeling analysis of the most common usages of nanoparticle targeting of macrophages in solid tumors. The data spans 20 years of literature, providing an extensive meta-analysis of the nanoparticle strategies. Our topic model found 6 distinct topics: Immune and TAMs, Nanoparticles, Imaging, Gene Delivery and Exosomes, Vaccines, and Multi-modal Therapies. We also found distinct nanoparticle usage, tumor types, and therapeutic trends across these topics. Moreover, we established that the topic model could be used to assign new papers into the existing topics, thereby creating a Living Review. This type of meta-analysis provides a useful assessment tool for aggregating data about a large field.

The expendables: Bioarchaeological evidence for pauper apprentices in 19th century England and the health consequences of child labour.

Child labour is the most common form of child abuse in the world today, with almost half of child workers employed in hazardous industries. The large-scale employment of children during the rapid industrialisation of the late 18th and early 19th centuries in England is well documented. During this period, the removal of pauper children from workhouses in cities to work as apprentices in rural mills in the North of England was commonplace. Whilst the experiences of some of these children have been recorded historically, this study provides the first direct evidence of their lives through bioarchaeological analysis. The excavation of a rural churchyard cemetery in the village of Fewston, North Yorkshire, yielded the skeletal remains of 154 individuals, including an unusually large proportion of children aged between 8 to 20 years. A multi-method approach was undertaken, including osteological and palaeopathological examination, stable isotope and amelogenin peptide analysis. The bioarchaeological results were integrated with historical data regarding a local textile mill in operation during the 18th-19th centuries. The results for the children were compared to those obtained from contemporaneous individuals of known identity (from coffin plates) of comparable date. Most of the children exhibited distinctive 'non-local' isotope signatures and a diet low in animal protein when compared to the named local individuals. These children also showed severe growth delays and pathological lesions indicative of early life adversity, as well as respiratory disease, which is a known occupational hazard of mill work. This study has provided unique insights into the harrowing lives of these children; born into poverty and forced to work long hours in dangerous conditions. This analysis provides a stark testimony of the impacts of industrial labour on the health, growth and mortality risk of children, with implications for the present as well as our understanding of the past.

Leveraging Coupled Solvatofluorochromism and Fluorescence Quenching in Nitrophenyl-Containing Thiazolothiazoles for Efficient Organic Vapor Sensing.

Solvatofluorochromic molecules provide strikingly high fluorescent outputs to monitor a wide range of biological, environmental, or materials-related sensing processes. Here, thiazolo[5,4-d]thiazole (TTz) fluorophores equipped with simple alkylamino and nitrophenyl substituents for solid-state, high-performance chemo-responsive sensing applications are reported. Nitroaromatic substituents are known to strongly quench dye fluorescence, however, the TTz core subtly modulates intramolecular charge transfer (ICT) enabling strong, locally excited-state fluorescence in non-polar conditions. In polar media, a planar ICT excited-state shows near complete quenching, enabling a twisted excited-state emission to be observed. These unique fluorescent properties (spectral shifts of 0.13 - 0.87 eV and large transition dipole moments Δµ = 20.4 - 21.3 D) are leveraged to develop highly sought-after chemo-responsive, organic vapor optical sensors. The sensors are developed by embedding the TTz fluorophores within a poly(styrene-isoprene-styrene) block copolymer to form fluorescent dye/polymer composites (ΦF = 70 - 97%). The composites respond reversibly to a comprehensive list of organic solvents and show low vapor concentration sensing (e.g., 0.04% solvent saturation vapor pressure of THF - 66 ppm). The composite films can distinguish between solvent vapors with near complete fluorescent quenching observed when exposed to their saturated solvent vapor pressures, making this an extremely promising material for optical chemo-responsive sensing.

Evaluating Listening Performance for COVID-19 Detection by Clinicians and Machine Learning: Comparative Study.

BACKGROUND: To date, performance comparisons between men and machines have been carried out in many health domains. Yet machine learning (ML) models and human performance comparisons in audio-based respiratory diagnosis remain largely unexplored. OBJECTIVE: The primary objective of this study was to compare human clinicians and an ML model in predicting COVID-19 from respiratory sound recordings. METHODS: In this study, we compared human clinicians and an ML model in predicting COVID-19 from respiratory sound recordings. Prediction performance on 24 audio samples (12 tested positive) made by 36 clinicians with experience in treating COVID-19 or other respiratory illnesses was compared with predictions made by an ML model trained on 1162 samples. Each sample consisted of voice, cough, and breathing sound recordings from 1 subject, and the length of each sample was around 20 seconds. We also investigated whether combining the predictions of the model and human experts could further enhance the performance in terms of both accuracy and confidence. RESULTS: The ML model outperformed the clinicians, yielding a sensitivity of 0.75 and a specificity of 0.83, whereas the best performance achieved by the clinicians was 0.67 in terms of sensitivity and 0.75 in terms of specificity. Integrating the clinicians' and the model's predictions, however, could enhance performance further, achieving a sensitivity of 0.83 and a specificity of 0.92. CONCLUSIONS: Our findings suggest that the clinicians and the ML model could make better clinical decisions via a cooperative approach and achieve higher confidence in audio-based respiratory diagnosis.

Long term outcomes following kidney transplantation in children who weighed less than 15 kg - report from the UK Transplant Registry.

BACKGROUND: Kidney transplantation is the treatment of choice in chronic kidney disease (CKD) stage 5. It is often delayed in younger children until a target weight is achieved due to technical feasibility and historic concerns about poorer outcomes. METHODS: Data on all first paediatric (aged < 18 years) kidney only transplants performed in the United Kingdom between 1 January 2006 and 31 December 2016 were extracted from the UK Transplant Registry (n = 1,340). Children were categorised by weight at the time of transplant into those < 15 kg and those ≥ 15 kg. Donor, recipient and transplant characteristics were compared between groups using chi-squared or Fisher's exact test for categorical variables and Kruskal-Wallis test for continuous variables. Thirty day, one-year, five-year and ten-year patient and kidney allograft survival were compared using the Kaplan-Meier method. RESULTS: There was no difference in patient survival following kidney transplantation when comparing children < 15 kg with those ≥ 15 kg. Ten-year kidney allograft survival was significantly better for children < 15 kg than children ≥ 15 kg (85.4% vs. 73.5% respectively, p = 0.002). For children < 15 kg, a greater proportion of kidney transplants were from living donors compared with children ≥ 15 kg (68.3% vs. 49.6% respectively, p < 0.001). There was no difference in immediate graft function between the groups (p = 0.54) and delayed graft function was seen in 4.8% and 6.8% of children < 15 kg and ≥ 15 kg respectively. CONCLUSIONS: Our study reports significantly better ten-year kidney allograft survival in children < 15 kg and supports consideration of earlier transplantation for children with CKD stage 5. A higher resolution version of the Graphical abstract is available as Supplementary information.

An Automated, Online Feasibility Randomized Controlled Trial of a Just-In-Time Adaptive Intervention for Smoking Cessation (Quit Sense).

INTRODUCTION: Learned smoking cues from a smoker's environment are a major cause of lapse and relapse. Quit Sense, a theory-guided Just-In-Time Adaptive Intervention smartphone app, aims to help smokers learn about their situational smoking cues and provide in-the-moment support to help manage these when quitting. METHODS: A two-arm feasibility randomized controlled trial (N = 209) to estimate parameters to inform a definitive evaluation. Smoker's willing to make a quit attempt were recruited using online paid-for adverts and randomized to "usual care" (text message referral to NHS SmokeFree website) or "usual care" plus a text message invitation to install Quit Sense. Procedures, excluding manual follow-up for nonresponders, were automated. Follow-up at 6 weeks and 6 months included feasibility, intervention engagement, smoking-related, and economic outcomes. Abstinence was verified using cotinine assessment from posted saliva samples. RESULTS: Self-reported smoking outcome completion rates at 6 months were 77% (95% CI 71%, 82%), viable saliva sample return rate was 39% (95% CI 24%, 54%), and health economic data 70% (95% CI 64%, 77%). Among Quit Sense participants, 75% (95% CI 67%, 83%) installed the app and set a quit date and, of those, 51% engaged for more than one week. The 6-month biochemically verified sustained abstinence rate (anticipated primary outcome for definitive trial), was 11.5% (12/104) among Quit Sense participants and 2.9% (3/105) for usual care (adjusted odds ratio = 4.57, 95% CIs 1.23, 16.94). No evidence of between-group differences in hypothesized mechanisms of action was found. CONCLUSIONS: Evaluation feasibility was demonstrated alongside evidence supporting the effectiveness potential of Quit Sense. IMPLICATIONS: Running a primarily automated trial to initially evaluate Quit Sense was feasible, resulting in modest recruitment costs and researcher time, and high trial engagement. When invited, as part of trial participation, to install a smoking cessation app, most participants are likely to do so, and, for those using Quit Sense, an estimated one-half will engage with it for more than 1 week. Evidence that Quit Sense may increase verified abstinence at 6-month follow-up, relative to usual care, was generated, although low saliva return rates to verify smoking status contributed to considerable imprecision in the effect size estimate.

Unbearable suffering while working as a nurse during the COVID-19 pandemic: A qualitative descriptive study.

Background: The COVID-19 pandemic resulted in negative consequences for nurse well-being, patient care delivery and outcomes, and organizational outcomes. Objective: The purpose of this study was to explore the experiences of nurses working during the COVID-19 Pandemic in the United States. Design: This study used a qualitative descriptive design. Settings: The setting for this study was a national sample of nurses working during the COVID-19 pandemic in the United States over a period of 18 months. Participants: Convenience and snowball sampling were used to recruit 81 nurses via social media and both national and state listservs. Methods: Using a single question prompt, voicemail and emails were used for nurses to share their experiences anonymously working as a nurse during the COVID-19 pandemic. Voicemails were transcribed and each transcript was analyzed using content analysis with both deductive and inductive coding. Results: The overarching theme identified was Unbearable Suffering. Three additional themes were identified: 1) Facilitators to Nursing Practice During the COVID-19 Pandemic, 2) Barriers to Nursing Practice During the COVID-19 pandemic, with the sub-themes of Barriers Within the Work Environment, Suboptimal Care Delivery, and Negative Consequences for the Nurses; and lastly, 3) the Transitionary Nature of the Pandemic.. Conclusions: The primary finding of this study was that nurses experienced and witnessed unbearable suffering while working during the COVID-19 pandemic that was transitionary in nature. Future research should consider the long-term impacts of this unbearable suffering on nurses. Intervention research should be considered to support nurses who have worked during the COVID-19 pandemic, and mitigate the potential long-term effects. Tweetable abstract: A study on nurses experiences during the pandemic reveals their unbearable suffering. Read here about the reasons nurses are leaving.

A summary of the ComParE COVID-19 challenges.

The COVID-19 pandemic has caused massive humanitarian and economic damage. Teams of scientists from a broad range of disciplines have searched for methods to help governments and communities combat the disease. One avenue from the machine learning field which has been explored is the prospect of a digital mass test which can detect COVID-19 from infected individuals' respiratory sounds. We present a summary of the results from the INTERSPEECH 2021 Computational Paralinguistics Challenges: COVID-19 Cough, (CCS) and COVID-19 Speech, (CSS).

Detecting tropical peatland degradation: Combining remote sensing and organic geochemistry.

Tropical peatlands are important carbon stores that are vulnerable to drainage and conversion to agriculture. Protection and restoration of peatlands are increasingly recognised as key nature based solutions that can be implemented as part of climate change mitigation. Identification of peatland areas that are important for protection and restauration with regards to the state of their carbon stocks, are therefore vital for policy makers. In this paper we combined organic geochemical analysis by Rock-Eval (6) pyrolysis of peat collected from sites with different land management history and optical remote sensing products to assess if remotely sensed data could be used to predict peat conditions and carbon storage. The study used the North Selangor Peat Swamp forest, Malaysia, as the model system. Across the sampling sites the carbon stocks in the below ground peat was ca 12 times higher than the forest (median carbon stock held in ground vegetation 114.70 Mg ha-1 and peat soil 1401.51 Mg ha-1). Peat core sub-samples and litter collected from Fire Affected, Disturbed Forest, and Managed Recovery locations (i.e. disturbed sites) had different decomposition profiles than Central Forest sites. The Rock-Eval pyrolysis of the upper peat profiles showed that surface peat layers at Fire Affected, Disturbed Forest, and Managed Recovery locations had lower immature organic matter index (I-index) values (average I-index range in upper section 0.15 to -0.06) and higher refractory organic matter index (R -index) (average R-index range in upper section 0.51 to 0.65) compared to Central Forest sites indicating enhanced decomposition of the surface peat. In the top 50 cm section of the peat profile, carbon stocks were negatively related to the normalised burns ratio (NBR) (a satellite derived parameter) (Spearman's rho = -0.664, S = 366, p-value = <0.05) while there was a positive relationship between the hydrogen index and the normalised burns ratio profile (Spearman's rho = 0.7, S = 66, p-value = <0.05) suggesting that this remotely sensed product is able to detect degradation of peat in the upper peat profile. We conclude that the NBR can be used to identify degraded peatland areas and to support identification of areas for conversation and restoration.

Organ Transplants From Deceased Donors With Primary Brain Tumors and Risk of Cancer Transmission.

Importance: Cancer transmission is a known risk for recipients of organ transplants. Many people wait a long time for a suitable transplant; some never receive one. Although patients with brain tumors may donate their organs, opinions vary on the risks involved. Objective: To determine the risk of cancer transmission associated with organ transplants from deceased donors with primary brain tumors. Key secondary objectives were to investigate the association that donor brain tumors have with organ usage and posttransplant survival. Design, Setting, and Participants: This was a cohort study in England and Scotland, conducted from January 1, 2000, to December 31, 2016, with follow-up to December 31, 2020. This study used linked data on deceased donors and solid organ transplant recipients with valid national patient identifier numbers from the UK Transplant Registry, the National Cancer Registration and Analysis Service (England), and the Scottish Cancer Registry. For secondary analyses, comparators were matched on factors that may influence the likelihood of organ usage or transplant failure. Statistical analysis of study data took place from October 1, 2021, to May 31, 2022. Exposures: A history of primary brain tumor in the organ donor, identified from all 3 data sources using disease codes. Main Outcomes and Measures: Transmission of brain tumor from the organ donor into the transplant recipient. Secondary outcomes were organ utilization (ie, transplant of an offered organ) and survival of kidney, liver, heart, and lung transplants and their recipients. Key covariates in donors with brain tumors were tumor grade and treatment history. Results: This study included a total of 282 donors (median [IQR] age, 42 [33-54] years; 154 females [55%]) with primary brain tumors and 887 transplants from them, 778 (88%) of which were analyzed for the primary outcome. There were 262 transplants from donors with high-grade tumors and 494 from donors with prior neurosurgical intervention or radiotherapy. Median (IQR) recipient age was 48 (35-58) years, and 476 (61%) were male. Among 83 posttransplant malignancies (excluding NMSC) that occurred over a median (IQR) of 6 (3-9) years in 79 recipients of transplants from donors with brain tumors, none were of a histological type matching the donor brain tumor. Transplant survival was equivalent to that of matched controls. Kidney, liver, and lung utilization were lower in donors with high-grade brain tumors compared with matched controls. Conclusions and Relevance: Results of this cohort study suggest that the risk of cancer transmission in transplants from deceased donors with primary brain tumors was lower than previously thought, even in the context of donors that are considered as higher risk. Long-term transplant outcomes are favorable. These results suggest that it may be possible to safely expand organ usage from this donor group.

Testing to sustain hepatitis C elimination targets in people who inject drugs: A network-based model.

Little is known about the level of testing required to sustain elimination of hepatitis C (HCV), once achieved. In this study, we model the testing coverage required to maintain HCV elimination in an injecting network of people who inject drugs (PWID). We test the hypothesis that network-based strategies are a superior approach to deliver testing. We created a dynamic injecting network structure connecting 689 PWID based on empirical data. The primary outcome was the testing coverage required per month to maintain prevalence at the elimination threshold over 5 years. We compared four testing strategies. Without any testing or treatment provision, the prevalence of HCV increased from the elimination threshold (11.68%) to a mean of 25.4% (SD 2.96%) over the 5-year period. To maintain elimination with random testing, on average, 4.96% (SD 0.83%) of the injecting network needs to be tested per month. However, with a 'bring your friends' strategy, this was reduced to 3.79% (SD 0.64%) of the network (p < .001). The addition of contact tracing improved the efficiency of both strategies. In conclusion, we report that network-based approaches to testing such as 'bring a friend' initiatives and contact tracing lower the level of testing coverage required to maintain elimination.

Integrative Wellness Approaches to Mitigate Perceived Stress, Increase Vitality, and Build Community during COVID-19: A Pilot Study.

INTRODUCTION: In January 2020, a small, private school of nursing in a university in the pacific northwest, established the Initiative for Vital Practice (I4VP). The I4VP's primary goal was to create a sustainable pathway for increasing vital practice through increasing resiliency and self-care practices. OBJECTIVES: The ensuing pathway's objectives were to, (1) take previously identified factors related to perceived stress related to workloads, impacts on professional quality of life and psychosocial exposures during the COVID-19 pandemic; and (2) develop and pilot test a wellness intervention (i.e., wellness pods) for faculty and staff to build community and find new ways to enhance well-being through peer support. METHODS: Five focused Wellness Pods were developed on Microsoft Teams platform using the individual channels: (1) stress and mind-body exploration pod; (2) mindfulness in healthcare pod; (3) healing relationship pod; (4) environmental pod; and (5) physical activity pod. Faculty and staff self-selected into a Wellness Pod that interested them. The Wellness Pods met weekly in person over a period of two months. Quantitative and qualitative data was collected via cross-sectional surveys including: four sociodemographic items, one item on current stress level, one write-in item on current stress management at work, two write-in items focused on the cognitive reasoning for participation, the 7-item subjective vitality scale focused individual difference, the 7-item subjective vitality scale focused on the state level, the 10-item perceived stress scale, and one item ranking which wellness pod the individual wanted to participate in. There was one trained facilitator for the overall Wellness Pods operations and communication. RESULTS: The average score on the perceived stress scale was 22.3 (SD = 3.5), indicating moderate levels of perceived stress. The average score on the individual difference vitality score was 26.5 (SD = 7.6), whereas the state level vitality score was 21.4 (SD = 9.98), indicating moderate levels of subjective vitality. Two categories: stress management and wellness pods, were identified through content analysis. CONCLUSIONS: Through pilot testing, this project demonstrated feasibility for future wellness pods interventions for faculty and staff at schools of nursing. Future research is needed to evaluate the effectiveness of the wellness pods intervention.

Expanding the Mind-Body-Environment Connection to Enhance the Development of Cultural Humility.

The unique health care needs of diverse individuals and communities are complex. To meet these needs, healthcare professionals are being called upon to alter traditional ways of thinking, perceiving, and acting in order to create more inclusive environments. Research shows that using mindsight, a process that increases both insight and empathy, can enhance an individual's mind-body-environment connection, increase self-awareness, and promote the development of cultural humility. This paper will discuss the current perspectives on the mind/body/environment connection from a Western lens that may impact the enactment of cultural humility for healthcare providers. Two evidence-based approaches, yoga and forest therapy, are recommended as effective intervention tools in fostering mindsight and cultural humility. Blending traditional cognitive learning with techniques anchored in the physical body may hold promise in supporting the development of mindsight and cultural humility in healthcare education and practice.

New Advances on Wellness Therapies Using Integrated Health Focusing on Nature.

The purpose of this Special Issue is to provide you, the reader, with an overview of new advancements in wellness therapies using integrative health focusing on nature [...].

Exploring Longitudinal Cough, Breath, and Voice Data for COVID-19 Progression Prediction via Sequential Deep Learning: Model Development and Validation.

BACKGROUND: Recent work has shown the potential of using audio data (eg, cough, breathing, and voice) in the screening for COVID-19. However, these approaches only focus on one-off detection and detect the infection, given the current audio sample, but do not monitor disease progression in COVID-19. Limited exploration has been put forward to continuously monitor COVID-19 progression, especially recovery, through longitudinal audio data. Tracking disease progression characteristics and patterns of recovery could bring insights and lead to more timely treatment or treatment adjustment, as well as better resource management in health care systems. OBJECTIVE: The primary objective of this study is to explore the potential of longitudinal audio samples over time for COVID-19 progression prediction and, especially, recovery trend prediction using sequential deep learning techniques. METHODS: Crowdsourced respiratory audio data, including breathing, cough, and voice samples, from 212 individuals over 5-385 days were analyzed, alongside their self-reported COVID-19 test results. We developed and validated a deep learning-enabled tracking tool using gated recurrent units (GRUs) to detect COVID-19 progression by exploring the audio dynamics of the individuals' historical audio biomarkers. The investigation comprised 2 parts: (1) COVID-19 detection in terms of positive and negative (healthy) tests using sequential audio signals, which was primarily assessed in terms of the area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity, with 95% CIs, and (2) longitudinal disease progression prediction over time in terms of probability of positive tests, which was evaluated using the correlation between the predicted probability trajectory and self-reported labels. RESULTS: We first explored the benefits of capturing longitudinal dynamics of audio biomarkers for COVID-19 detection. The strong performance, yielding an AUROC of 0.79, a sensitivity of 0.75, and a specificity of 0.71 supported the effectiveness of the approach compared to methods that do not leverage longitudinal dynamics. We further examined the predicted disease progression trajectory, which displayed high consistency with longitudinal test results with a correlation of 0.75 in the test cohort and 0.86 in a subset of the test cohort with 12 (57.1%) of 21 COVID-19-positive participants who reported disease recovery. Our findings suggest that monitoring COVID-19 evolution via longitudinal audio data has potential in the tracking of individuals' disease progression and recovery. CONCLUSIONS: An audio-based COVID-19 progression monitoring system was developed using deep learning techniques, with strong performance showing high consistency between the predicted trajectory and the test results over time, especially for recovery trend predictions. This has good potential in the postpeak and postpandemic era that can help guide medical treatment and optimize hospital resource allocations. The changes in longitudinal audio samples, referred to as audio dynamics, are associated with COVID-19 progression; thus, modeling the audio dynamics can potentially capture the underlying disease progression process and further aid COVID-19 progression prediction. This framework provides a flexible, affordable, and timely tool for COVID-19 tracking, and more importantly, it also provides a proof of concept of how telemonitoring could be applicable to respiratory diseases monitoring, in general.