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PremiseEvolution of separate sexes from hermaphroditism often proceeds through gynodioecy, but genetic constraints on this process are poorly understood. Genetic (co-)variances and between-sex genetic correlations were used to predict evolutionary responses of multiple reproductive traits in a sexually dimorphic gynodioecious species, and predictions were compared with observed responses to artificial selection.MethodsSchiedea (Caryophyllaceae) is an endemic Hawaiian lineage with hermaphroditic, gynodioecious, subdioecious, and dioecious species. We measured genetic parameters of Schiedea salicaria and used them to predict evolutionary responses of 18 traits in hermaphrodites and females in response to artificial selection for increased male (stamen) biomass in hermaphrodites or increased female (carpel, capsule) biomass in females. Observed responses over two generations were compared with predictions in replicate lines of treatments and controls.ResultsIn only two generations, both stamen biomass in hermaphrodites and female biomass in females responded markedly to direct selection, supporting a key assumption of models for evolution of dioecy. Other biomass traits, pollen and ovule numbers, and inflorescence characters important in wind pollination evolved indirectly in response to selection on sex allocation. Responses generally followed predictions from multivariate selection models, with some responses unexpectedly large due to increased genetic correlations as selection proceeded.ConclusionsResults illustrate the power of artificial selection and utility of multivariate selection models incorporating sex differences. They further indicate that pollen and ovule numbers and inflorescence architecture could evolve in response to selection on biomass allocation to male versus female function, producing complex changes in plant phenotype as separate sexes evolve.

We aimed to develop deep learning models using longitudinal chest X-rays (CXRs) and clinical data to predict in-hospital mortality of COVID-19 patients in the intensive care unit (ICU).Six hundred fifty-four patients (212 deceased, 442 alive, 5645 total CXRs) were identified across two institutions. Imaging and clinical data from one institution were used to train five longitudinal transformer-based networks applying five-fold cross-validation. The models were tested on data from the other institution, and pairwise comparisons were used to determine the best-performing models.A higher proportion of deceased patients had elevated white blood cell count, decreased absolute lymphocyte count, elevated creatine concentration, and incidence of cardiovascular and chronic kidney disease. A model based on pre-ICU CXRs achieved an AUC of 0.632 and an accuracy of 0.593, and a model based on ICU CXRs achieved an AUC of 0.697 and an accuracy of 0.657. A model based on all longitudinal CXRs (both pre-ICU and ICU) achieved an AUC of 0.702 and an accuracy of 0.694. A model based on clinical data alone achieved an AUC of 0.653 and an accuracy of 0.657. The addition of longitudinal imaging to clinical data in a combined model significantly improved performance, reaching an AUC of 0.727 (p = 0.039) and an accuracy of 0.732.The addition of longitudinal CXRs to clinical data significantly improves mortality prediction with deep learning for COVID-19 patients in the ICU.• Deep learning was used to predict mortality in COVID-19 ICU patients. • Serial radiographs and clinical data were used. • The models could inform clinical decision-making and resource allocation.

IntroductionHarm reduction services, including methadone maintenance therapy (MMT), have been decentralized to Vietnam's community health care settings. This study aims to pilot test an intervention to facilitate decentralized harm reduction service delivery in Vietnam.MethodsThe research team conducted an intervention pilot between August 2020 and May 2021 with six community MMT distribution sites in Thai Nguyen Province of Vietnam. We recruited five commune health workers (CHW) from each center (N=30). In-person intervention training included content to correct misconceptions about harm reduction and reduce stigmatizing attitudes toward patients who use drugs and teach CHWs to self-examine and improve their service provision process. The study team developed a web-based platform to streamline CHW's patient monitoring and referral efforts. The team assessed intervention outcomes at baseline, 3-, and 6-months. CHWs in the intervention group provided acceptability ratings and feedback on the intervention at 6-months.ResultsCHWs in both intervention and control groups had similar background characteristics and outcome measures at baseline. CHWs in the intervention group, compared to those in the control group, showed a significantly higher level of improvement in adherence to service delivery protocol at 3-months. CHW in the intervention group had a significantly lower level of management-related stress compared to the control group at 6-months, although the intervention effect measured by the difference in change from baseline was not statistically significant. CHWs who participated in the final focus group reported high acceptability of the intervention.ConclusionThis intervention pilot demonstrated acceptability and promising outcomes on community-based harm reduction service delivery. Similar intervention strategies can be applied to enhance the decentralization of other chronic disease treatment services.

Traumatic brain injury (TBI) results in disrupted brain function following impact from an external force and is a risk factor for sporadic Alzheimer's disease (AD). Although neurologic symptoms triggered by mild traumatic brain injuries (mTBI), the most common form of TBI, typically resolve rapidly, even an isolated mTBI event can increase the risk to develop AD. Aberrant accumulation of amyloid β peptide (Aβ), a cleaved fragment of amyloid precursor protein (APP), is a key pathologic outcome designating the progression of AD following mTBI and has also been linked to impaired axonal transport. However, relationships among mTBI, amyloidogenesis, and axonal transport remain unclear, in part because of the dearth of human models to study the neuronal response following mTBI. Here, we implemented a custom-microfabricated device to deform neurons derived from human-induced pluripotent stem cells, derived from a cognitively unimpaired male individual, to mimic the mild stretch experienced by neurons during mTBI. Although no cell lethality or cytoskeletal disruptions were observed, mild stretch was sufficient to stimulate rapid amyloidogenic processing of APP. This processing led to abrupt cessation of APP axonal transport and progressive formation of aberrant axonal accumulations that contained APP, its processing machinery, and amyloidogenic fragments. Consistent with this sequence of events, stretch-induced defects were abrogated by reducing amyloidogenesis either pharmacologically or genetically. In sum, we have uncovered a novel and manipulable stretch-induced amyloidogenic pathway directly responsible for APP axonal transport dysregulation. Our findings may help to understand and ultimately mitigate the risk of developing AD following mTBI.SIGNIFICANCE STATEMENTMild traumatic brain injury is a risk factor for sporadic Alzheimer's disease (AD). Increased amyloid β peptide generation after injury may drive this risk. Here, by using a custom-built device to impose mild stretch to human neurons, we found that stretch triggers amyloid precursor protein (APP) cleavage, and thus amyloid β peptide generation, consequently disrupting APP axonal transport. Compellingly, protecting APP from cleavage was sufficient to spare axonal transport dysregulation and the consequent aberrant axonal accumulation of APP. Supporting such protective mechanism, the expression of the AD-protective APPA673Tgenetic variant conferred protection against stretch-induced APP axonal transport phenotypes. Our data reveal potential subcellular pathways contributing to the development of AD-associated phenotypes following mild traumatic brain injury, and putative strategies for intervening in these pathways.

OBJECTIVES To study the natural history of renal oncocytomas and address indications for intervention by determining how growth is associated with renal function over time, the reasons for surgery and ablation, and disease-specific survival. PATIENTS AND METHODS The study was conducted in a retrospective cohort of consecutive patients with renal oncocytoma on active surveillance reviewed at the Specialist Centre for Kidney Cancer at the Royal Free London NHS Foundation Trust (2012 to 2019). Comparison between groups was performed using Mann-Whitney U-tests and chi-squared tests. A mixed-effects model with a random intercept for patient was used to study the longitudinal association between tumour size and estimated glomerular filtration rate (eGFR). RESULTS Longitudinal data from 98 patients with 101 lesions were analysed. Most patients were men (68.3%) and the median (interquartile range [IQR]) age was 69 (13) years. The median (IQR) follow-up was 29 (26) months. Most lesions were small renal masses, and 24% measured over 4 cm. Over half (64.4%) grew at a median (IQR) rate of 2 (4) mm per year. No association was observed between tumour size and eGFR over time (P = 0.871). Nine lesions (8.9%) were subsequently treated. Two deaths were reported, neither were related to the diagnosis of renal oncocytoma. CONCLUSION Natural history data from the largest active surveillance cohort of renal oncocytomas to date show that renal function does not seem to be negatively impacted by growing oncocytomas, and confirms clinical outcomes are excellent after a median follow-up of over 2 years. Active surveillance should be considered the 'gold standard' management of renal oncocytomas up to 7cm.

Objectives Early recognition of coronavirus disease 2019 (COVID-19) severity can guide patient management. However, it is challenging to predict when COVID-19 patients will progress to critical illness. This study aimed to develop an artificial intelligence system to predict future deterioration to critical illness in COVID-19 patients. Methods An artificial intelligence (AI) system in a time-to-event analysis framework was developed to integrate chest CT and clinical data for risk prediction of future deterioration to critical illness in patients with COVID-19. Results A multi-institutional international cohort of 1,051 patients with RT-PCR confirmed COVID-19 and chest CT was included in this study. Of them, 282 patients developed critical illness, which was defined as requiring ICU admission and/or mechanical ventilation and/or reaching death during their hospital stay. The AI system achieved a C-index of 0.80 for predicting individual COVID-19 patients’ to critical illness. The AI system successfully stratified the patients into high-risk and low-risk groups with distinct progression risks (p < 0.0001). Conclusions Using CT imaging and clinical data, the AI system successfully predicted time to critical illness for individual patients and identified patients with high risk. AI has the potential to accurately triage patients and facilitate personalized treatment. Key Point • AI system can predict time to critical illness for patients with COVID-19 by using CT imaging and clinical data. Supplementary Information The online version contains supplementary material available at 10.1007/s00330-021-08049-8.

Lympho-epithelial interactions between intestinal T resident memory cells (Trm) and the epithelium have been associated with inflammatory bowel disease (IBD) activity. We developed ex vivo autologous organoid-mucosal T cell cocultures to functionally assess lymphoepithelial interactions in Crohn's Disease (CD) patients compared to controls. We demonstrate the direct epithelial cell death induced by autologous mucosal T cells in CD patients but not in controls. These findings were positively correlated with T cell infiltration of the organoids. This potential was inhibited by limiting lympho-epithelial interactions through CD103 and NKG2D blocking antibodies. These data directly demonstrate for the first time the direct deleterious effect of mucosal T cells on the epithelium of CD patients. Such ex-vivo models are promising techniques to unravel the pathophysiology of these diseases and the potential mode of action of current and future therapies. ispartof: FRONTIERS IN IMMUNOLOGY vol:13 ispartof: location:Switzerland status: published

Crude methanol extract of 9 Vietnamese plants were in vitro screened for their antibacterial activity against three common freshwater fish pathogens including Aeromonas hydrophila, Edwardsiella ictaluri, and Streptococcus agalactiae. Agar disc diffusion method was used to evaluate the antibacterial activity, then solvent extract was performed for the extracts which exhibited the strongest and a broad-spectrum antibacterial activity. Minimal inhibitory concentration (MIC) was conducted for effective plant extracts using broth dilution method. The results indicated that most of the plant extracts exhibited antibacterial propeties to at least one tested bacterium. Headache tree (Premna corymbosa), bushwillows (Combretum quadrangulare) and Celandine spider flower (Cleome chelidonii) showed a broad-spectrum antibacterial activity. The largest inhibitory zones of 35 mm and 21 mm were observed for the extract of Premna corymbosa against E. ictaluri and S. agalactiae, respectively. E. ictaluri was found to be the most susceptible for all of the extracts while A. hydrophila was the most resistant. The MIC of effective plant extracts against tested bacteria ranged between 0.39 mg/mL and 3.125 mg/mL. The result can be considered for further investigation of the development of an alternative therapy against bacterial infection in aquaculture.

Aims To determine if neurologic symptoms at admission can predict adverse outcomes in patients with severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2). Methods Electronic medical records of 1053 consecutively hospitalized patients with laboratory‐confirmed infection of SARS‐CoV‐2 from one large medical center in the USA were retrospectively analyzed. Univariable and multivariable Cox regression analyses were performed with the calculation of areas under the curve (AUC) and concordance index (C‐index). Patients were stratified into subgroups based on the presence of encephalopathy and its severity using survival statistics. In sensitivity analyses, patients with mild/moderate and severe encephalopathy (defined as coma) were separately considered. Results Of 1053 patients (mean age 52.4 years, 48.0% men [n = 505]), 35.1% (n = 370) had neurologic manifestations at admission, including 10.3% (n = 108) with encephalopathy. Encephalopathy was an independent predictor for death (hazard ratio [HR] 2.617, 95% confidence interval [CI] 1.481–4.625) in multivariable Cox regression. The addition of encephalopathy to multivariable models comprising other predictors for adverse outcomes increased AUCs (mortality: 0.84–0.86, ventilation/ intensive care unit [ICU]: 0.76–0.78) and C‐index (mortality: 0.78 to 0.81, ventilation/ICU: 0.85–0.86). In sensitivity analyses, risk stratification survival curves for mortality and ventilation/ICU based on severe encephalopathy (n = 15) versus mild/moderate encephalopathy (n = 93) versus no encephalopathy (n = 945) at admission were discriminative (p, Patients with severe acute respiratory syndrome coronavirus 2 infection have a high prevalence of neurologic manifestations, including headache, encephalopathy, dizziness, taste, and smell impairment. Patients with encephalopathy at admission predict later progression to death and mechanical ventilation/ICU admission in SARS‐CoV‐2 infection, which may have important implications for risk stratification in clinical practice.

The study aims to investigate the impact of participation in decision-making (PDM) and perceived organizational support (POS) on affective commitment in machinery enterprises. The study applies structural equation modeling (SEM) to test the research hypotheses. The authors surveyed 220 employees who work in machinery enterprises to collect data for the research. The study results indicate that both PDM and POS positively impact affective commitment. The findings provide empirical evidence to support the theoretical models that PDM and POS have a positive effect on affective commitment. The findings have implications for management theory: PDM and POS are the key antecedents of affective commitment. The findings also have implications for practical management in the machinery enterprises that managers should practice both PDM and POS to increase affective commitment.

The My Aged Care website, established by the Australian Government, is the starting point for aged care consumers and carers to find information on aged care providers. Using information published on this platform, we compile a unique dataset of 588 approved home care providers in Queensland. This article presents a brief introduction to this dataset, including how they are extracted and what variables are available. We propose some current and future applications of this data with a focus on how it can contribute to evidence‐based policymaking in Australia.

Background Coronavirus disease 2019 (COVID-19) and pneumonia of other diseases share similar CT characteristics, which contributes to the challenges in differentiating them with high accuracy. Purpose To establish and evaluate an artificial intelligence (AI) system for differentiating COVID-19 and other pneumonia at chest CT and assessing radiologist performance without and with AI assistance. Materials and Methods A total of 521 patients with positive reverse transcription polymerase chain reaction results for COVID-19 and abnormal chest CT findings were retrospectively identified from 10 hospitals from January 2020 to April 2020. A total of 665 patients with non-COVID-19 pneumonia and definite evidence of pneumonia at chest CT were retrospectively selected from three hospitals between 2017 and 2019. To classify COVID-19 versus other pneumonia for each patient, abnormal CT slices were input into the EfficientNet B4 deep neural network architecture after lung segmentation, followed by a two-layer fully connected neural network to pool slices together. The final cohort of 1186 patients (132 583 CT slices) was divided into training, validation, and test sets in a 7:2:1 and equal ratio. Independent testing was performed by evaluating model performance in separate hospitals. Studies were blindly reviewed by six radiologists without and then with AI assistance. Results The final model achieved a test accuracy of 96% (95% confidence interval [CI]: 90%, 98%), a sensitivity of 95% (95% CI: 83%, 100%), and a specificity of 96% (95% CI: 88%, 99%) with area under the receiver operating characteristic curve of 0.95 and area under the precision-recall curve of 0.90. On independent testing, this model achieved an accuracy of 87% (95% CI: 82%, 90%), a sensitivity of 89% (95% CI: 81%, 94%), and a specificity of 86% (95% CI: 80%, 90%) with area under the receiver operating characteristic curve of 0.90 and area under the precision-recall curve of 0.87. Assisted by the probabilities of the model, the radiologists achieved a higher average test accuracy (90% vs 85%, Δ = 5

Background Despite its high sensitivity in diagnosing COVID-19 in a screening population, chest CT appearances of COVID 19 pneumonia are thought to be non-specific. Purpose To assess the performance of United States (U.S.) and Chinese radiologists in differentiating COVID-19 from viral pneumonia on chest CT. Methods A total of 219 patients with both positive COVID-19 by RT-PCR and abnormal chest CT findings were retrospectively identified from 7 Chinese hospitals in Hunan Providence, China from January 6 to February 20, 2020. A total of 205 patients with positive Respiratory Pathogen Panel for viral pneumonia and CT findings consistent with or highly suspicious for pneumonia by original radiology interpretation within 7 days of each other were identified from Rhode Island Hospital in Providence, RI. Three Chinese radiologists blindly reviewed all chest CTs (n=424) to differentiate COVID-19 from viral pneumonia. A sample of 58 age-matched cases was randomly selected and evaluated by 4 U.S. radiologists in a similar fashion. Different CT features were recorded and compared between the two groups. Results For all chest CTs, three Chinese radiologists correctly differentiated COVID-19 from non-COVID-19 pneumonia 83% (350/424), 80% (338/424), and 60% (255/424) of the time, respectively. The seven radiologists had sensitivities of 80%, 67%, 97%, 93%, 83%, 73% and 70% and specificities of 100%, 93%, 7%, 100%, 93%, 93%, 100%. Compared to non-COVID-19 pneumonia, COVID-19 pneumonia was more likely to have a peripheral distribution (80% vs. 57%, p

Humoral hypercalcemia of malignancy is rarely seen in urothelial cancer. In this report, we present a case of an 81-year-old female patient who presented with a markedly elevated calcium level leading to severe altered mental status and was found to have urothelial cancer. To our knowledge, only three cases of urothelial carcinoma with squamous cell differentiation have been reported.

Background: Atrial fibrillation (AF) and heart failure (HF) frequently coexist and can be challenging to treat. Pharmacologically based rhythm control of AF has not proven to be superior to rate control. Ablation-based rhythm control was compared with rate control to evaluate if clinical outcomes in patients with HF and AF could be improved. Methods: This was a multicenter, open-label trial with blinded outcome evaluation using a central adjudication committee. Patients with high-burden paroxysmal (>4 episodes in 6 months) or persistent (duration Results: From December 1, 2011, to January 20, 2018, 411 patients were randomly assigned to ablation-based rhythm control (n=214) or rate control (n=197). The primary outcome occurred in 50 (23.4%) patients in the ablation-based rhythm-control group and 64 (32.5%) patients in the rate-control group (hazard ratio, 0.71 [95% CI, 0.49–1.03]; P =0.066). Left ventricular ejection fraction increased in the ablation-based group (10.1±1.2% versus 3.8±1.2%, P =0.017), 6-minute walk distance improved (44.9±9.1 m versus 27.5±9.7 m, P =0.025), and NT-proBNP demonstrated a decrease (mean change –77.1% versus –39.2%, P P =0.0036), as did the AF Effect on Quality of Life score (least-squares mean difference of 6.2 [95% CI, 1.7–10.7]; P =0.0005). Serious adverse events were observed in 50% of patients in both treatment groups. Conclusions: In patients with high-burden AF and HF, there was no statistical difference in all-cause mortality or HF events with ablation-based rhythm control versus rate control; however, there was a nonsignificant trend for improved outcomes with ablation-based rhythm control over rate control. Registration: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT01420393.

Background and Purpose: Hypertension is a known risk factor that accelerates and leads to cardiovascular disease. While it is often a risk factor recognized in middle-aged and older adults, it is overlooked in young adults. The purpose of this study was to (1) implement a mHealth intervention, the O ptimize B lood Pressure I mprovement ( MOBI LE) intervention, in college students, aged 18 to 29 years, with elevated blood pressure (BP); and (2) test its feasibility and impact on BP reduction (primary outcome) along with sodium intake and hypertension knowledge improvement (secondary outcomes) after 28 days. Methods: The pilot study used a two-arm, randomized controlled trial. Subjects in the intervention group were required to monitor their daily BP. We recruited full-time students who had regular access to a mobile smartphone with unlimited texting and elevated BP or undiagnosed hypertension stage I. We excluded students who were pregnant, lactating, planning to become pregnant during the study, taking antihypertensive medication, or diagnosed with a life-threatening illness or condition associated with hypertension. We conducted the formative phase before the intervention phase to assess the acceptability, engagement, and feasibility of the intervention motivational text messages. During the educational session for baseline data, all subjects completed a sociodemographic questionnaire, the Automated Self-Administered 24-Hour Dietary Assessment Tool (ASA24), and the Hypertension Knowledge-Level Scale. Following, all subjects’ height and weight were also collected to calculate body mass index. For 28 days, subjects in the intervention group provided their daily BP measurement using the Withings wireless BP cuff and their motivational levels (1 for low motivation, 3 for moderate motivation, and 5 for high motivation) to receive the appropriate text message. After 28 days, all subjects were scheduled for an exit interview to collect post intervention data along with an exit interview. The control group completed the educational session and exit interview only. Results: Twenty-nine participants (intervention: n = 15; control: n = 14) completed the study. We found a significant decrease in BP in the intervention group ( p = 0.001) while no statistical significance was found in the control group. Using the ASA24 to extract sodium intake, there was no statistical difference in sodium intake for intervention or control groups. The mean hypertension knowledge score increased in both groups after 28 days; however, the improvement was only significant for the control group ( p = 0.001). Conclusions: The results provided preliminary data on the effect of BP reduction in both groups with more impact on the intervention group. These promising findings warrant further examination of the intervention and its long-term effects.

While COVID-19 diagnosis and prognosis artificial intelligence models exist, very few can be implemented for practical use given their high risk of bias. We aimed to develop a diagnosis model that addresses notable shortcomings of prior studies, integrating it into a fully automated triage pipeline that examines chest radiographs for the presence, severity, and progression of COVID-19 pneumonia. Scans were collected using the DICOM Image Analysis and Archive, a system that communicates with a hospital’s image repository. The authors collected over 6,500 non-public chest X-rays comprising diverse COVID-19 severities, along with radiology reports and RT-PCR data. The authors provisioned one internally held-out and two external test sets to assess model generalizability and compare performance to traditional radiologist interpretation. The pipeline was evaluated on a prospective cohort of 80 radiographs, reporting a 95% diagnostic accuracy. The study mitigates bias in AI model development and demonstrates the value of an end-to-end COVID-19 triage platform.

Novel phenanthridinone analogs with an all-carbon quaternary stereocenter have been enantioselectively synthesized using the Birch-Heck sequence. Flat phenanthridinone structures have extensive bioactivity, but consequently also suffer from poor therapeutic selectivity. The addition of a quaternary center to the phenanthridinone skeleton has the potential to generate more complex analogs with improved selectivity. Unfortunately, no general synthetic pathway to such derivatives exists. Herein we report a four-step process that transforms inexpensive benzoic acid into twenty-two different quaternary carbon containing phenanthridinone analogs with a variety of substituents on all three rings: alkyl groups at the quaternary center; methyl, methoxymethyl or para-methoxybenzyl on the amide nitrogen; and halogen and methyl substituents on the aryl ring. Good to very good enantioselectivity was demonstrated in the key intramolecular desymmetrizing Mizoroki-Heck reaction. Transformations of the Heck reaction products into molecules with potentially greater therapeutic relevance were also accomplished.

Background: Phase III trials have demonstrated the efficacy of risankizumab in moderate-to-severe Crohn's disease (CD), but no real-world data are currently available. We aimed to assess the short-term effectiveness and safety of risankizumab in patients with CD.Methods: From May 2021 to May 2022, all patients with refractory luminal CD treated with risankizumab in 22 French GETAID centres were retrospectively included. The primary endpoint was steroid-free clinical remission at week 12 (Harvey-Bradshaw [HB] score

BACKGROUND AND AIMS: There is a need to evaluate the benefit-risk ratio of current therapies in inflammatory bowel disease (IBD) patients to provide the best quality of care. The primary objective of I-CARE (IBD Cancer and serious infections in Europe) was to assess prospectively safety concerns in IBD, with specific focus on the risk of cancer/lymphoma and serious infections in patients treated with anti-tumor necrosis factor and other biologic monotherapy as well as in combination with immunomodulators.METHODS: I-CARE was designed as a European prospective longitudinal observational multicenter cohort study to include patients with a diagnosis of Crohn's disease, ulcerative colitis, or IBD unclassified established at least 3 months prior to enrollment.RESULTS: A total of 10,206 patients were enrolled between March 2016 and April 2019, including 6169 (60.4%) patients with Crohn's disease, 3853 (37.8%) with ulcerative colitis, and 184 (1.8%) with a diagnosis of IBD unclassified. Thirty-two percent of patients were receiving azathioprine/thiopurines, 4.6% 6-mercaptopurine, and 3.2% methotrexate at study entry. At inclusion, 47.3% of patients were treated with an anti-tumor necrosis factor agent, 8.8% with vedolizumab, and 3.4% with ustekinumab. Roughly one-quarter of patients (26.8%) underwent prior IBD-related surgery. Sixty-six percent of patients had been previously treated with systemic steroids. Three percent of patients had a medical history of cancer prior to inclusion and 1.1% had a history of colonic, esophageal, or uterine cervix high-grade dysplasia.CONCLUSIONS: I-CARE is an ongoing investigator-initiated observational European prospective cohort study that will provide unique information on the long-term benefits and risks of biological therapies in IBD patients. (EudraCT, Number: 2014-004728-23; ClinicalTrials.gov, Number: NCT02377258).

Vietnam’s Payment for Forest Ecosystem Services (PFES) scheme has the goal of protecting remaining natural forests by providing financial support to people involved in forest protection. However, studying the case of Dak Lak province in the Central Highlands region of Vietnam shows that even after eight years of PFES implementation, achieving this goal remains a challenge. Although PFES does provide a stable income source and higher payments than state forest protection programs, enables the mobilization of more personnel resources for patrolling forest and relieves a great burden on the state budget in terms of investment in forest protection and development, forest cover in Dak Lak province is still decreasing, mainly due to conversion for other land uses, especially commercial agricultural and industrial crops. These drivers are rooted in national socio-economic planning aimed at boosting economic growth and in local people’s need to sustain their livelihoods. In addition, our paper shows that illegal logging is still widespread in Dak Lak. Weak law enforcement in areas of forest managed by state forest authorities and state companies also contributes to deforestation. However, these drivers are neither fully recognized nor addressed, and instead, the blame for deforestation is laid on local communities. PFES alone cannot protect forests in Dak Lak province. It needs to be backed up by political commitment to address underlying drivers of deforestation, improved social programs to help local people diversify their income sources and clarity over land use.