The Ecology of Rawa Aopa, a Peat-swamp in Sulawesi, Indonesia

Rawa Aopa is a large swamp in South-East Sulawesi, Indonesia — the only major peat-swamp in this mainly mountainous island. Its vegetation and fauna are still quite poorly known. The existing information is summarized here. With the creation of new villages as part of Indonesia's transmigration programme, the human population in this area has increased very rapidly. Pressure on natural resources — especially soils and forests — is increasing, and primary forests are dwindling rapidly. This in turn increases the threats to Rawa Aopa, as erosion in its catchment area inevitably leads to a rapid silting up of the swamp. The swamp has a potential as a source of food (fish and sago) and income (rattan and other products), and it might to some degree become a tourist attraction. From a scientific point of view, the gaps in the knowledge about water-regime, vegetation, and fauna, ought to be remedied. In order to attain sustainable utilization of this area, a thorough plan ought to be made for the whole catchment of Rawa Aopa. The most important measure to take is the protection of the forests covering the hills and the surroundings of the swamp. Also important very widely is the protection of soils. Furthermore, it is recommended to include the northern part of the swamp in the already-existing Rawa Aopa—Watumohai National Par

Dose-Volume Histogram Parameters and Quality of Life in Patients with Prostate Cancer Treated with Surgery and High-Dose Volumetric-Intensity-Modulated Arc Therapy to the Prostate Bed.

INTRODUCTION Prostate bed radiotherapy (RT) is a major affecter of patients' long-term quality of life (QoL). To ensure the best possible outcome of these patients, dose constraints are key for optimal RT planning and delivery. However, establishing refined dose constraints requires access to patient-level data. Therefore, we aimed to provide such data on the relationship between OAR and gastrointestinal (GI) as well as genitourinary (GU) QoL outcomes of a homogenous patient cohort who received dose-intensified post-operative RT to the prostate bed. Furthermore, we aimed to conduct an exploratory analysis of the resulting data. METHODS Patients who were treated with prostate bed RT between 2010 and 2020 were inquired about their QoL based on the Expanded Prostate Cancer Index Composite (EPIC). Those (n = 99) who received volumetric arc therapy (VMAT) of at least 70 Gy to the prostate bed were included. Dose-volume histogram (DVH) parameters were gathered and correlated with the EPIC scores. RESULTS The median age at the time of prostate bed RT was 68.9 years, and patients were inquired about their QoL in the median 2.3 years after RT. The median pre-RT prostate-specific antigen (PSA) serum level was 0.35 ng/mL. The median duration between surgery and RT was 1.5 years. The median prescribed dose to the prostate bed was 72 Gy. A total of 61.6% received prostate bed RT only. For the bladder, the highest level of statistical correlation (p < 0.01) was seen for V10-20Gy, Dmean and Dmedian with urinary QoL. For bladder wall, the highest level of statistically significant correlation (p < 0.01) was seen for V5-25Gy, Dmean and Dmedian with urinary QoL. Penile bulb V70Gy was statistically significantly correlated with sexual QoL (p < 0.05). A larger rectal volume was significantly correlated with improved bowel QoL (p < 0.05). Sigmoid and urethral DVH parameters as well as the surgical approach were not statistically significantly correlated with QoL. CONCLUSION Specific dose constraints for bladder volumes receiving low doses seem desirable for the further optimization of prostate bed RT. This may be particularly relevant in the context of the aspiration of establishing focal RT of prostate cancer and its local recurrences. Our comprehensive dataset may aid future researchers in achieving these goals

Applications of Machine Learning in Palliative Care: A Systematic Review.

Objective: To summarize the available literature on using machine learning (ML) for palliative care practice as well as research and to assess the adherence of the published studies to the most important ML best practices. Methods: The MEDLINE database was searched for the use of ML in palliative care practice or research, and the records were screened according to PRISMA guidelines. Results: In total, 22 publications using machine learning for mortality prediction (n = 15), data annotation (n = 5), predicting morbidity under palliative therapy (n = 1), and predicting response to palliative therapy (n = 1) were included. Publications used a variety of supervised or unsupervised models, but mostly tree-based classifiers and neural networks. Two publications had code uploaded to a public repository, and one publication uploaded the dataset. Conclusions: Machine learning in palliative care is mainly used to predict mortality. Similarly to other applications of ML, external test sets and prospective validations are the exception

Applications of Machine Learning in Palliative Care: A Systematic Review

Objective: To summarize the available literature on using machine learning (ML) for palliative care practice as well as research and to assess the adherence of the published studies to the most important ML best practices. Methods: The MEDLINE database was searched for the use of ML in palliative care practice or research, and the records were screened according to PRISMA guidelines. Results: In total, 22 publications using machine learning for mortality prediction (n = 15), data annotation (n = 5), predicting morbidity under palliative therapy (n = 1), and predicting response to palliative therapy (n = 1) were included. Publications used a variety of supervised or unsupervised models, but mostly tree-based classifiers and neural networks. Two publications had code uploaded to a public repository, and one publication uploaded the dataset. Conclusions: Machine learning in palliative care is mainly used to predict mortality. Similarly to other applications of ML, external test sets and prospective validations are the exception

Convolutional Neural Networks to Detect Vestibular Schwannomas on Single MRI Slices: A Feasibility Study.

In this study. we aimed to detect vestibular schwannomas (VSs) in individual magnetic resonance imaging (MRI) slices by using a 2D-CNN. A pretrained CNN (ResNet-34) was retrained and internally validated using contrast-enhanced T1-weighted (T1c) MRI slices from one institution. In a second step, the model was externally validated using T1c- and T1-weighted (T1) slices from a different institution. As a substitute, bisected slices were used with and without tumors originating from whole transversal slices that contained part of the unilateral VS. The model predictions were assessed based on the categorical accuracy and confusion matrices. A total of 539, 94, and 74 patients were included for training, internal validation, and external T1c validation, respectively. This resulted in an accuracy of 0.949 (95% CI 0.935-0.963) for the internal validation and 0.912 (95% CI 0.866-0.958) for the external T1c validation. We suggest that 2D-CNNs might be a promising alternative to 2.5-/3D-CNNs for certain tasks thanks to the decreased demand for computational power and the fact that there is no need for segmentations. However, further research is needed on the difference between 2D-CNNs and more complex architectures

Mathematical treatment of adiabatic fast passage pulses for the computation of nuclear spin relaxation rates in proteins with conformational exchange

Although originally designed for broadband inversion and decoupling in NMR spectroscopy, recent methodological developments have introduced adiabatic fast passage (AFP) pulses into the field of protein dynamics. AFP pulses employ a frequency sweep, and have not only superior inversion properties with respect to offset effects, but they are also easily implemented into a pulse sequence. As magnetization is dragged from the +z to the −z direction, Larmor precession is impeded since magnetization becomes spin-locked, which is a potentially useful feature for the investigation of microsecond to millisecond dynamics. A major drawback of these pulses as theoretical prediction is concerned, however, results from their time-dependent offset: simulations of spin density matrices under the influence of a time-dependent Hamiltonian with non-commuting elements are costly in terms of computational time, rendering data analysis impracticable. In this paper we suggest several ways to reduce the computational time without compromising accuracy with respect to effects such as cross-correlated relaxation and modulation of the chemical shift

Consequences of Exchanging Carbohydrates for Proteins in the Cholesterol Metabolism of Mice Fed a High-fat Diet

Consumption of low-carbohydrate, high-protein, high-fat diets lead to rapid weight loss but the cardioprotective effects of these diets have been questioned. We examined the impact of high-protein and high-fat diets on cholesterol metabolism by comparing the plasma cholesterol and the expression of cholesterol biosynthesis genes in the liver of mice fed a high-fat (HF) diet that has a high (H) or a low (L) protein-to-carbohydrate (P/C) ratio. H-P/C-HF feeding, compared with L-P/C-HF feeding, decreased plasma total cholesterol and increased HDL cholesterol concentrations at 4-wk. Interestingly, the expression of genes involved in hepatic steroid biosynthesis responded to an increased dietary P/C ratio by first down-regulation (2-d) followed by later up-regulation at 4-wk, and the temporal gene expression patterns were connected to the putative activity of SREBF1 and 2. In contrast, Cyp7a1, the gene responsible for the conversion of cholesterol to bile acids, was consistently up-regulated in the H-P/C-HF liver regardless of feeding duration. Over expression of Cyp7a1 after 2-d and 4-wk H-P/C-HF feeding was connected to two unique sets of transcription regulators. At both time points, up-regulation of the Cyp7a1 gene could be explained by enhanced activations and reduced suppressions of multiple transcription regulators. In conclusion, we demonstrated that the hypocholesterolemic effect of H-P/C-HF feeding coincided with orchestrated changes of gene expressions in lipid metabolic pathways in the liver of mice. Based on these results, we hypothesize that the cholesterol lowering effect of high-protein feeding is associated with enhanced bile acid production but clinical validation is warranted. (246 words

Ticagrelor Monotherapy or Dual Antiplatelet Therapy After Drug-Eluting Stent Implantation: Per-Protocol Analysis of the GLOBAL LEADERS Trial.

Background In the GLOBAL LEADERS trial, ticagrelor monotherapy beyond 1 month compared with standard antiplatelet regimens after coronary stent implantation did not improve outcomes at intention-to-treat analysis. Considerable differences in treatment adherence between the experimental and control groups may have affected the intention-to-treat results. In this reanalysis of the GLOBAL LEADERS trial, we compared the experimental and control treatment strategies in a per-protocol analysis of patients who did not deviate from the study protocol. Methods and Results Baseline and postrandomization information were used to classify whether and when patients were deviating from the study protocol. With logistic regressions, we derived time-varying inverse probabilities of nondeviation from protocol to reconstruct the trial population without protocol deviation. The primary end point was a composite of all-cause mortality or nonfatal Q-wave myocardial infarction at 2 years. At 2-year follow-up, 1103 (13.8%) of 7980 patients in the experimental group and 785 (9.8%) of 7988 patients in the control group qualified as protocol deviators. At per-protocol analysis, the rate ratio for the primary end point was 0.88 (95% CI, 0.75-1.03; P=0.10) on the basis of 274 versus 325 events in the experimental versus control group. The rate ratio for the key safety end point of major bleeding was 1.00 (95% CI, 0.79-1.26; P=0.99). The per-protocol and intention-to-treat effect estimates were overall consistent. Conclusions Among patients who complied with the study protocol in the GLOBAL LEADERS trial, ticagrelor plus aspirin for 1 month followed by ticagrelor monotherapy was not superior to 1-year standard dual antiplatelet therapy followed by aspirin alone at 2 years after coronary stenting. Registration URL: https://www.clinicaltrials.gov; Unique identifier: NCT01813435

Changing Incidence and Risk Factors for Kaposi Sarcoma by Time Since Starting Antiretroviral Therapy: Collaborative Analysis of 21 European Cohort Studies.

BACKGROUND:  Kaposi sarcoma (KS) remains a frequent cancer in human immunodeficiency virus (HIV)-positive patients starting combination antiretroviral therapy (cART). We examined incidence rates and risk factors for developing KS in different periods after starting cART in patients from European observational HIV cohorts. METHODS:  We included HIV-positive adults starting cART after 1 January 1996. We analyzed incidence rates and risk factors for developing KS up to 90 and 180 days and 1, 2, 5, and 8 years after cART start and fitted univariable and multivariable Cox regression models. RESULTS:  We included 109 461 patients from 21 prospective clinical cohorts in Europe with 916 incident KS cases. The incidence rate per 100 000 person-years was highest 6 months after starting cART, at 953 (95% confidence interval, 866-1048), declining to 82 (68-100) after 5-8 years. In multivariable analyses adjusted for exposure group, origin, age, type of first-line regimen, and calendar year, low current CD4 cell counts increased the risk of developing KS throughout all observation periods after cART initiation. Lack of viral control was not associated with the hazard of developing KS in the first year after cART initiation, but was over time since starting cART increasingly positively associated (P < .001 for interaction). CONCLUSION:  In patients initiating cART, both incidence and risk factors for KS change with time since starting cART. Whereas soon after starting cART low CD4 cell count is the dominant risk factor, detectable HIV-1 RNA viral load becomes an increasingly important risk factor in patients who started cART several years earlier, independently of immunodeficiency