Benthic foraminifera show some resilience to ocean acidification in the northern Gulf of California, Mexico.

The version on PEARL: Corrected proofs are Articles in Press that contain the authors' corrections. Final citation details, e.g., volume/issue number, publication year and page numbers, still need to be added and the text might change before final publication. Although corrected proofs do not have all bibliographic details available yet, they can already be cited using the year of online publication and the DOI , as follows: author(s), article title, journal (year), DOIExtensive CO2 vents have been discovered in the Wagner Basin, northern Gulf of California, where they create large areas with lowered seawater pH. Such areas are suitable for investigations of long-term biological effects of ocean acidification and effects of CO2 leakage from subsea carbon capture storage. Here, we show responses of benthic foraminifera to seawater pH gradients at 74-207m water depth. Living (rose Bengal stained) benthic foraminifera included Nonionella basispinata, Epistominella bradyana and Bulimina marginata. Studies on foraminifera at CO2 vents in the Mediterranean and off Papua New Guinea have shown dramatic long-term effects of acidified seawater. We found living calcareous benthic foraminifera in low pH conditions in the northern Gulf of California, although there was an impoverished species assemblage and evidence of post-mortem test dissolution

Candidate‐Gene Study of Functional Polymorphisms in SLCO1B1 and CYP3A4/5 and the Cholesterol‐Lowering Response to Simvastatin

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/137517/1/cts12432.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/137517/2/cts12432_am.pd

Dietary patterns and the risk of obesity, type 2 diabetes mellitus, cardiovascular diseases, asthma, and neurodegenerative diseases

Diet and lifestyle play a significant role in the development chronic diseases; however the full complexity of this relationship is not yet understood. Dietary pattern investigation, which reflects the complexity of dietary intake, has emerged as an alternative and complementary approach for examining the association between diet and chronic diseases. Literature on this association has largely focused on individual nutrients, with conflicting outcomes, but individuals consume a combination of foods from many groups that form dietary patterns. Our objective was to systematically review the current findings on the effects of dietary patterns on chronic diseases. In this review, we describe and discuss the relationships between dietary patterns, such as the Mediterranean, the Dietary Approach to Stop Hypertension, Prudent, Seventh-day Adventists, and Western, with risk of obesity, type-2 diabetes mellitus, cardiovascular diseases, asthma, and neurodegenearive diseases. Evidence is increasing from both observational and clinical studies that plant-based dietary patterns, which are rich in fruits, vegetables, and whole grains, are valuable in preventing various chronic diseases, whereas a diet high in red and processed meat, refined grains and added sugar seems to increase said risk. Dietary pattern analysis might be especially valuable to the development and evaluation of food-based dietary guidelines

Analytic Kramer kernels, Lagrange-type interpolation series and de Branges spaces

The classical Kramer sampling theorem provides a method for obtaining orthogonal sampling formulas. In particular, when the involved kernel is analytic in the sampling parameter it can be stated in an abstract setting of reproducing kernel Hilbert spaces of entire functions which includes as a particular case the classical Shannon sampling theory. This abstract setting allows us to obtain a sort of converse result and to characterize when the sampling formula associated with an analytic Kramer kernel can be expressed as a Lagrange-type interpolation series. On the other hand, the de Branges spaces of entire functions satisfy orthogonal sampling formulas which can be written as Lagrange-type interpolation series. In this work some links between all these ideas are established

The Antioxidant Potential of the Mediterranean Diet in Patients at High Cardiovascular Risk: An In-Depth Review of the PREDIMED

Cardiovascular disease (CVD) is the leading global cause of death. Diet is known to be important in the prevention of CVD. The PREDIMED trial tested a relatively low-fat diet versus a high-fat Mediterranean diet (MedDiet) for the primary prevention of CVD. The resulting reduction of the CV composite outcome resulted in a paradigm shift in CV nutrition. Though many dietary factors likely contributed to this effect, this review focuses on the influence of the MedDiet on endogenous antioxidant systems and the effect of dietary polyphenols. Subgroup analysis of the PREDIMED trial revealed increased endogenous antioxidant and decreased pro-oxidant activity in the MedDiet groups. Moreover, higher polyphenol intake was associated with lower incidence of the primary outcome, overall mortality, blood pressure, inflammatory biomarkers, onset of new-onset type 2 diabetes mellitus (T2DM), and obesity. This suggests that polyphenols likely contributed to the lower incidence of the primary event in the MedDiet groups. In this article, we summarize the potential benefits of polyphenols found in the MedDiet, specifically the PREDIMED cohort. We also discuss the need for further research to confirm and expand the findings of the PREDIMED in a non-Mediterranean population and to determine the exact mechanisms of action of polyphenols

CHRONOFALLS: A multicentre nurse-led intervention in the chronoprevention of in-hospital falls in adults

Background: Falls are among the most common and serious adverse events for hospitalised patients. In-hospital falls pose a major medical and economic challenge for public health worldwide. Nevertheless, the issue is often addressed without regard to certain relevant variables such as the time of the fall. The aim of this study was to determine the effect of the implementation of a nurse-led intervention based on the temporal patterns of falls and their aetiology on the occurrence of falls. Methods: A mixed-method research design was carried out in three phases: a) a longitudinal prospective study (audits, chronobiological analyses and implementation of a multicentre nurse-led intervention based on temporal patterns of falls); b) a retrospective study of fall records; and c) a qualitative study based on focus groups. The protocol was published in 2021. Results: A difference was observed in the number of fall records before and after the chronopreventive intervention (retrospective: 64.4% vs. 35.6%; p < 0,001). According to the interrupted series analysis, considering the influence of the COVID-19 pandemic, a reduction in falls of 2.96% (95% CI 1.70%-4.17%) was observed. The concepts of falls, the COVID-19 pandemic and the causes of non-registration have emerged as categories for qualitative analysis. Conclusions: A multicentric nurse-led program based on tailored organisational, educational and behavioural chronopreventive measures seems to lead to a reduction in the number of in-hospital falls. The findings of the present study, highlighting the implementation of chronopreventive measures, can serve as a basis for future health policies

Risk score for first-screening of prevalent undiagnosed chronic kidney disease in Peru: the CRONICAS-CKD risk score.

BACKGROUND: Chronic Kidney Disease (CKD) represents a great burden for the patient and the health system, particularly if diagnosed at late stages. Consequently, tools to identify patients at high risk of having CKD are needed, particularly in limited-resources settings where laboratory facilities are scarce. This study aimed to develop a risk score for prevalent undiagnosed CKD using data from four settings in Peru: a complete risk score including all associated risk factors and another excluding laboratory-based variables. METHODS: Cross-sectional study. We used two population-based studies: one for developing and internal validation (CRONICAS), and another (PREVENCION) for external validation. Risk factors included clinical- and laboratory-based variables, among others: sex, age, hypertension and obesity; and lipid profile, anemia and glucose metabolism. The outcome was undiagnosed CKD: eGFR < 60 ml/min/1.73m2. We tested the performance of the risk scores using the area under the receiver operating characteristic (ROC) curve, sensitivity, specificity, positive/negative predictive values and positive/negative likelihood ratios. RESULTS: Participants in both studies averaged 57.7 years old, and over 50% were females. Age, hypertension and anemia were strongly associated with undiagnosed CKD. In the external validation, at a cut-off point of 2, the complete and laboratory-free risk scores performed similarly well with a ROC area of 76.2% and 76.0%, respectively (P = 0.784). The best assessment parameter of these risk scores was their negative predictive value: 99.1% and 99.0% for the complete and laboratory-free, respectively. CONCLUSIONS: The developed risk scores showed a moderate performance as a screening test. People with a score of ≥ 2 points should undergo further testing to rule out CKD. Using the laboratory-free risk score is a practical approach in developing countries where laboratories are not readily available and undiagnosed CKD has significant morbidity and mortality

Complexity without chaos: Plasticity within random recurrent networks generates robust timing and motor control

It is widely accepted that the complex dynamics characteristic of recurrent neural circuits contributes in a fundamental manner to brain function. Progress has been slow in understanding and exploiting the computational power of recurrent dynamics for two main reasons: nonlinear recurrent networks often exhibit chaotic behavior and most known learning rules do not work in robust fashion in recurrent networks. Here we address both these problems by demonstrating how random recurrent networks (RRN) that initially exhibit chaotic dynamics can be tuned through a supervised learning rule to generate locally stable neural patterns of activity that are both complex and robust to noise. The outcome is a novel neural network regime that exhibits both transiently stable and chaotic trajectories. We further show that the recurrent learning rule dramatically increases the ability of RRNs to generate complex spatiotemporal motor patterns, and accounts for recent experimental data showing a decrease in neural variability in response to stimulus onset