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The goal of this study is to detect linear and nonlinear causal pathways toward climate change as measured by changes in global mean surface temperature and global mean sea level over time using a data-based approach in contrast to the traditional physics-based models. Monthly data on potential climate change causal factors, including greenhouse gas concentrations, sunspot numbers, humidity, ice sheets mass, and sea ice coverage, from January 2003 to December 2021, have been utilized in the analysis. We first applied the vector autoregressive model (VAR) and Granger causality test to gauge the linear Granger causal relationships among climate factors. We then adopted the vector error correction model (VECM) as well as the autoregressive distributed lag model (ARDL) to quantify the linear long-run equilibrium and the linear short-term dynamics. Cointegration analysis has also been adopted to examine the dual directional Granger causalities. Furthermore, in this work, we have presented a novel pipeline based on the artificial neural network (ANN) and the VAR and ARDL models to detect nonlinear causal relationships embedded in the data. The results in this study indicate that the global sea level rise is affected by changes in ice sheet mass (both linearly and nonlinearly), global mean temperature (nonlinearly), and the extent of sea ice coverage (nonlinearly and weakly); whereas the global mean temperature is affected by the global surface mean specific humidity (both linearly and nonlinearly), greenhouse gas concentration as measured by the global warming potential (both linearly and nonlinearly) and the sunspot number (only nonlinearly and weakly). Furthermore, the nonlinear neural network models tend to fit the data closer than the linear models as expected due to the increased parameter dimension of the neural network models. Given that the information criteria are not generally applicable to the comparison of neural network models and statistical time series models, our next step is to examine the robustness and compare the forecast accuracy of these two models using the soon-available 2022 monthly data.

Abstract In this work, we focus on using reinforcement learning and game theory to solve for the optimal strategies for the dice game Pig, in a novel simultaneous playing setting. First, we derived analytically the optimal strategy for the 2-player simultaneous game using dynamic programming, mixed-strategy Nash equilibrium. At the same time, we proposed a new Stackelberg value iteration framework to approximate the near-optimal pure strategy. Next, we developed the corresponding optimal strategy for the multiplayer independent strategy game numerically. Finally, we presented the Nash equilibrium for simultaneous Pig game with infinite number of players. To help promote the learning of and interest in reinforcement learning, game theory and statistics, we have further implemented a website where users can play both the sequential and simultaneous Pig game against the optimal strategies derived in this work.

Purpose: Intravoxel incoherent motion (IVIM) is a quantitative magnetic resonance imaging (MRI) method used to quantify perfusion properties of tissue non-invasively without contrast. However, clinical applications are limited by unreliable parameter estimates, particularly for the perfusion fraction (f) and pseudodiffusion coefficient (D*). This study aims to develop a high-fidelity reconstruction for reliable estimation of IVIM parameters. The proposed method is versatile and amenable to various acquisition schemes and fitting methods. Methods: To address current challenges with IVIM, we adapted several advanced reconstruction techniques. We used a low-rank approximation of IVIM images and temporal subspace modeling to constrain the magnetization dynamics of the bi-exponential diffusion signal decay. In addition, motion-induced phase variations were corrected between diffusion directions and b-values, facilitating the use of high SNR real-valued diffusion data. The proposed method was evaluated in simulations and in vivo brain acquisitions in six healthy subjects and six individuals with a history of SARS-CoV-2 infection and compared with the conventionally reconstructed magnitude data. Following reconstruction, IVIM parameters were estimated voxel-wise. Results: Our proposed method reduced noise contamination in simulations, resulting in a 60%, 58.9%, and 83.9% reduction in the NRMSE for D, f, and D*, respectively, compared to the conventional reconstruction. In vivo, anisotropic properties of D, f, and D* were preserved with the proposed method, highlighting microvascular differences in gray matter between individuals with a history of COVID-19 and those without (p = 0.0210), which wasn't observed with the conventional reconstruction. Conclusion: The proposed method yielded a more reliable estimation of IVIM parameters with less noise than the conventional reconstruction. Further, the proposed method preserved anisotropic properties of IVIM parameter estimates and demonstrated differences in microvascular perfusion in COVID-affected subjects, which weren't observed with conventional reconstruction methods.

The objective of this study is to evaluate the efficacy of deep learning (DL) techniques in improving the quality of diffusion MRI (dMRI) data in clinical applications. The study aims to determine whether the use of artificial intelligence (AI) methods in medical images may result in the loss of critical clinical information and/or the appearance of false information. To assess this, the focus was on the angular resolution of dMRI and a clinical trial was conducted on migraine, specifically between episodic and chronic migraine patients. The number of gradient directions had an impact on white matter analysis results, with statistically significant differences between groups being drastically reduced when using 21 gradient directions instead of the original 61. Fourteen teams from different institutions were tasked to use DL to enhance three diffusion metrics (FA, AD and MD) calculated from data acquired with 21 gradient directions and a b-value of 1000 s/mm2. The goal was to produce results that were comparable to those calculated from 61 gradient directions. The results were evaluated using both standard image quality metrics and Tract-Based Spatial Statistics (TBSS) to compare episodic and chronic migraine patients. The study results suggest that while most DL techniques improved the ability to detect statistical differences between groups, they also led to an increase in false positive. The results showed that there was a constant growth rate of false positives linearly proportional to the new true positives, which highlights the risk of generalization of AI-based tasks when assessing diverse clinical cohorts and training using data from a single group. The methods also showed divergent performance when replicating the original distribution of the data and some exhibited significant bias. In conclusion, extreme caution should be exercised when using AI methods for harmonization or synthesis in clinical studies when processing heterogeneous data in clinical studies, as important information may be altered, even when global metrics such as structural similarity or peak signal-to-noise ratio appear to suggest otherwise.

North Sumatera is one of the provinces in Indonesia with the highest buffalo population, which is responsible for the high accumulation of buffalo manure that can cause environmental and aesthetic problems if left untreated. One of the possible alternatives for solving this issue is by implementing buffalo manure as growth media for microorganisms, e.g. microalgae. In this research, buffalo manure was used as alternative media for Arthospira platensis cultivation. Buffalo manure was taken from Sitoluama village, Laguboti, Toba Regency of North Sumatra Province. Research steps included media and culture preparation, cultivation, sampling, sample analysis and verification of constructed models and validation. Buffalo manure concentration in media is varied from 1 g.L-1 to 8 g.L-1 which is analogous to nitrogen content of 0.002 mg.L-1 to 0.018 mg.L-1. Growth data was used for growth kinetic modelling, which was most satisfactory for Monod model (µmax = 0.5915 day-1, Ks = 0.421 g.L-1).

Proton exchange provides a powerful contrast mechanism for magnetic resonance imaging (MRI). MRI techniques sensitive to proton exchange provide new opportunities to map, with high spatial and temporal resolution, compounds important for brain metabolism and function. Two such techniques, chemical exchange saturation transfer (CEST) and T1 relaxation in the rotating frame (T1ρ), are emerging as promising tools in the study of neurological and psychiatric illnesses to study brain metabolism. This review describes proton exchange for non-experts, highlights the current status of proton-exchange MRI, and presents advantages and drawbacks of these techniques compared to more traditional methods of imaging brain metabolism, including positron emission tomography (PET) and MR spectroscopy (MRS). Finally, this review highlights new frontiers for the use of CEST and T1ρ in brain research.

Background Dengue shock syndrome (DSS) is characterized by severe vascular leakage and hemostasis disorder, which causes death in 1-5% of cases. World Health Organization management guidelines for fluid resuscitation in DSS remain empirical, rather than evidence-based. Objective To as sess the efficacy of ge latin compared to hydroxyethyl starch (HES) 130/0.4 solution for fluid resuscitation in children with DSS. Methods We performed a multi-centered, randomized study to compare gelatin and HES 130/0.4 solution for resuscitation of children with DSS. We randomly assigned 25 children with DSS to receive gelatin fluid and 25 children to receive HES 130/0.4. Statistical analyses were performed using Chi-square and MannWhitney tests. Results More rapid increase in pulse pressure was noted in subjects treated with HES 130/0.4 compared to those treated with gelatin at 8 hours and 28 hours of therapy (P=0.037 and P=0.048). The decrease in hematocrit in subjects treated with HES 130/0.4 was faster than that of gelatin at 4 hours of therapy (P=0.001). One patient died due to an unusual manifestation of DSS. Respiratory rate decreased faster in subjects treated with HES 130/0.4 than those treated with gelatin at 4 hours and 8 hours of therapy (P< 0.05). Body temperature remained higher in subjects treated with gelatin than HES 130/0.4 at 36 hours and 48 hours of therapy (P< 0.05). However, the decrease in platelet counts in subjects treated with HES 130/0.4 was more than that of gelatin (P=0.018). Conclusion HES 130/0.4 solution may be better for volume replacement compared to gelatin and is safe for fluid resuscitation in children with DSS.

In the present study, we examined the potential symptomatic and/or disease-modifying effects of monthly bee venom injections compared to placebo in moderatly affected Parkinson disease patients. We conducted a prospective, randomized double-blind study in 40 Parkinson disease patients at Hoehn & Yahr stages 1.5 to 3 who were either assigned to monthly bee venom injections or equivalent volumes of saline (treatment/placebo group: n = 20/20). The primary objective of this study was to assess a potential symptomatic effect of s.c. bee venom injections (100 μg) compared to placebo 11 months after initiation of therapy on United Parkinson’s Disease Rating Scale (UPDRS) III scores in the « off » condition pre-and post-injection at a 60 minute interval. Secondary objectives included the evolution of UPDRS III scores over the study period and [123I]-FP-CIT scans to evaluate disease progression. Finally, safety was assessed by monitoring specific IgE against bee venom and skin tests when necessary. After an 11 month period of monthly administration, bee venom did not significantly decrease UPDRS III scores in the « off » condition. Also, UPDRS III scores over the study course, and nuclear imaging, did not differ significantly between treatment groups. Four patients were excluded during the trial due to positive skin tests but no systemic allergic reaction was recorded. After an initial increase, specific IgE against bee venom decreased in all patients completing the trial. This study did not evidence any clear symptomatic or disease-modifying effects of monthly bee venom injections over an 11 month period compared to placebo using a standard bee venom allergy desensitization protocol in Parkinson disease patients. However, bee venom administration appeared safe in non-allergic subjects. Thus, we suggest that higher administration frequency and possibly higher individual doses of bee venom may reveal its potency in treating Parkinson disease.ClinicalTrials.gov NCT01341431.

[This corrects the article DOI: 10.1371/journal.pone.0158235.].

Abstract This single-station, standardized case assesses the medical knowledge and communication skills of an intern and/or fourth-year medical student in answering a mock page. The authors developed this case as an objective method to assess professionalism and communication skills through the use of a common clinical scenario in the health care system: a page from a nurse about patient care (an infected central venous catheter). This case can be administered as a stand-alone assessment or included as a station in an OSCE. The mock page scenario was created to mimic a naturally occurring communication episode between the learner and a nurse. In this scenario, a standardized nurse was used in the interaction. The authors created a checklist to emphasize items that demonstrate professionalism and communication skills. Medical knowledge checklist items were developed to assess the learner's ability to correctly identify and manage the clinical scenario of an infected indwelling venous catheter. This station was part of a six-station OSCE performed during the fourth-year medical school sub-internship rotation. This case has also been used during OSCEs administered to residents at the beginning and end of the intern year. Each examinee was provided with written instructions on the door of the station room. Using the checklist, in which items were equally weighted, the nurse assessed each learner during a 3-minute break between interactions. Scores were reported as percent correct on the 12-item checklist. Formative educational feedback on students' performance was provided to the learner, the sub-internship directors, and the director of the fourth year. Feedback on the interns' performance was provided to the interns and to their program directors. This feedback allowed medical students to identify areas for self-improvement as they progressed to the intern year, and it allowed individual program directors to reflect on and potentially modify their educational curricula.