Do you understand what I want to tell you? Early sensitivity in bilinguals' iconic gesture perception and production

Previous research has shown differences in monolingual and bilingual communication. We explored whether monolingual and bilingual pre‐schoolers (N = 80) differ in their ability to understand others' iconic gestures (gesture perception) and produce intelligible iconic gestures themselves (gesture production) and how these two abilities are related to differences in parental iconic gesture frequency. In a gesture perception task, the experimenter replaced the last word of every sentence with an iconic gesture. The child was then asked to choose one of four pictures that matched the gesture as well as the sentence. In a gesture production task, children were asked to indicate ‘with their hands’ to a deaf puppet which objects to select. Finally, parental gesture frequency was measured while parents answered three different questions. In the iconic gesture perception task, monolingual and bilingual children did not differ. In contrast, bilinguals produced more intelligible gestures than their monolingual peers. Finally, bilingual children's parents gestured more while they spoke than monolingual children's parents. We suggest that bilinguals' heightened sensitivity to their interaction partner supports their ability to produce intelligible gestures and results in a bilingual advantage in iconic gesture production

A novel therapeutic option in Cogan diseases? TNF-α blockers

Cogan's syndrome is characterized by non-infectious, interstitial keratitis combined with a vestibulo-auditory deficit. Despite therapy with corticosteroids in combination with immunosuppressive agents, relapses occurred in two subjects and the clinical course suggested a progression of the disease. Treatment with anti-TNF-α was started leading to a rapid and sustained clinical remission for over 2 respectively 3year

Potentially Diagnostic Electron Paramagnetic Resonance Spectra Elucidate the Underlying Mechanism of Mitochondrial Dysfunction in the Deoxyguanosine Kinase Deficient Rat Model of a Genetic Mitochondrial DNA Depletion Syndrome

A novel rat model for a well-characterized human mitochondrial disease, mitochondrial DNA depletion syndrome with associated deoxyguanosine kinase (DGUOK) deficiency, is described. The rat model recapitulates the pathologic and biochemical signatures of the human disease. The application of electron paramagnetic (spin) resonance (EPR) spectroscopy to the identification and characterization of respiratory chain abnormalities in the mitochondria from freshly frozen tissue of the mitochondrial disease model rat is introduced. EPR is shown to be a sensitive technique for detecting mitochondrial functional abnormalities in situ and, here, is particularly useful in characterizing the redox state changes and oxidative stress that can result from depressed expression and/or diminished specific activity of the distinct respiratory chain complexes. As EPR requires no sample preparation or non-physiological reagents, it provides information on the status of the mitochondrion as it was in the functioning state. On its own, this information is of use in identifying respiratory chain dysfunction; in conjunction with other techniques, the information from EPR shows how the respiratory chain is affected at the molecular level by the dysfunction. It is proposed that EPR has a role in mechanistic pathophysiological studies of mitochondrial disease and could be used to study the impact of new treatment modalities or as an additional diagnostic tool

Soliton and black hole solutions of su(N) Einstein-Yang-Mills theory in anti-de Sitter space

We present new soliton and hairy black hole solutions of su(N) Einstein-Yang-Mills theory in asymptotically anti-de Sitter space. These solutions are described by N+1 independent parameters, and have N-1 gauge field degrees of freedom. We examine the space of solutions in detail for su(3) and su(4) solitons and black holes. If the magnitude of the cosmological constant is sufficiently large, we find solutions where all the gauge field functions have no zeros. These solutions are of particular interest because we anticipate that at least some of them will be linearly stable.Comment: 15 pages, 20 figures, minor changes, accepted for publication in Physical Review

Direct and indirect effects of vertical mixing, nutrients and ultraviolet radiation on the bacterioplankton metabolism in high-mountain lakes from southern Europe

As a consequence of global change, modifications in the interaction among abiotic stressors on aquatic ecosystems have been predicted. Among other factors, UVR transparency, nutrient inputs and shallower epilimnetic layers could alter the trophic links in the microbial food web. Currently, there are some evidences of higher sensitiveness of aquatic microbial organisms to UVR in opaque lakes. Our aim was to assess the interactive direct and indirect effects of UVR (through the excretion of organic carbon – EOC – by algae), mixing regime and nutrient input on bacterial metabolism. We performed in situ short-term experiments under the following treatments: full sunlight (UVR + PAR, >280 nm) vs. UVR exclusion (PAR only, >400 nm); ambient vs. nutrient addition (phosphorus (P; 30 μg PL−1) and nitrogen (N; up to final N : P molar ratio of 31)); and static vs. mixed regime. The experiments were conducted in three high-mountain lakes of Spain: Enol [LE], Las Yeguas [LY] and La Caldera [LC] which had contrasting UVR transparency characteristics (opaque (LE) vs. clear lakes (LY and LC)). Under ambient nutrient conditions and static regimes, UVR exerted a stimulatory effect on heterotrophic bacterial production (HBP) in the opaque lake but not in the clear ones. Under UVR, vertical mixing and nutrient addition HBP values were lower than under the static and ambient nutrient conditions, and the stimulatory effect that UVR exerted on HBP in the opaque lake disappeared. By contrast, vertical mixing and nutrient addition increased HBP values in the clear lakes, highlighting for a photoinhibitory effect of UVR on HBP. Mixed regime and nutrient addition resulted in negative effects of UVR on HBP more in the opaque than in the clear lakes. Moreover, in the opaque lake, bacterial respiration (BR) increased and EOC did not support the bacterial carbon demand (BCD). In contrast, bacterial metabolic costs did not increase in the clear lakes and the increased nutrient availability even led to higher HBP. Consequently, EOC satisfied BCD in the clear lakes, particularly in the clearest one [LC]. Our results suggest that the higher vulnerability of bacteria to the damaging effects of UVR may be particularly accentuated in the opaque lakes and further recognizes the relevance of light exposure history and biotic interactions on bacterioplankton metabolism when coping with fluctuating radiation and nutrient inputs.Fil: Durán, C.. Universidad de Granada; EspañaFil: Medina Sánchez, J. M.. Universidad de Granada; EspañaFil: Herrera, G.. Universidad de Granada; EspañaFil: Villar Argaiz , M.. Universidad de Granada; EspañaFil: Villafañe, Virginia Estela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico; ArgentinaFil: Helbling, Eduardo Walter. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico; ArgentinaFil: Carrillo, P.. Universidad de Granada; Españ

Multiple interacting environmental drivers reduce the impact of solar UVR on primary productivity in Mediterranean lakes

Increases in rainfall, continental runoff, and atmospheric dust deposition are reducing water transparency in lakes worldwide (i.e. higher attenuation Kd). Also, ongoing alterations in multiple environmental drivers due to global change are unpredictably impacting phytoplankton responses and lakes functioning. Although both issues demand urgent research, it remains untested how the interplay between Kd and multiple interacting drivers affect primary productivity (Pc). We manipulated four environmental drivers in an in situ experiment—quality of solar ultraviolet radiation (UVR), nutrient concentration (Nut), CO2 partial pressure (CO2), and light regime (Mix)—to determine how the Pc of nine freshwater phytoplankton communities, found along a Kd gradient in Mediterranean ecosystems, changed as the number of interacting drivers increased. Our findings indicated that UVR was the dominant driver, its effect being between 3–60 times stronger, on average, than that of any other driver tested. Also, UVR had the largest difference in driver magnitude of all the treatments tested. A future UVR × CO2 × Mix × Nut scenario exerted a more inhibitory effect on Pc as the water column became darker. However, the magnitude of this synergistic effect was 40–60% lower than that exerted by double and triple interactions and by UVR acting independently. These results illustrate that although future global-change conditions could reduce Pc in Mediterranean lakes, multiple interacting drivers can temper the impact of a severely detrimental driver (i.e. UVR), particularly as the water column darkensMinisterio de Ciencia, Innovación y Universidades | Ref. FJCI2017-32318Ministerio de Economía y Competitividad | Ref. CGL2015-67682-RMinisterio de Economía y Competitividad | Ref. CGL2011-23681Ministerio de Medio Ambiente y Medio Rural y Marino | Ref. PN2009/067Junta de Andalucía | Ref. P09-RNM-5376Junta de Andalucía | Ref. Excelencia CVI-0259

Modality Attention and Sampling Enables Deep Learning with Heterogeneous Marker Combinations in Fluorescence Microscopy

Fluorescence microscopy allows for a detailed inspection of cells, cellular networks, and anatomical landmarks by staining with a variety of carefully-selected markers visualized as color channels. Quantitative characterization of structures in acquired images often relies on automatic image analysis methods. Despite the success of deep learning methods in other vision applications, their potential for fluorescence image analysis remains underexploited. One reason lies in the considerable workload required to train accurate models, which are normally specific for a given combination of markers, and therefore applicable to a very restricted number of experimental settings. We herein propose Marker Sampling and Excite, a neural network approach with a modality sampling strategy and a novel attention module that together enable ($i$) flexible training with heterogeneous datasets with combinations of markers and ($ii$) successful utility of learned models on arbitrary subsets of markers prospectively. We show that our single neural network solution performs comparably to an upper bound scenario where an ensemble of many networks is na\"ively trained for each possible marker combination separately. In addition, we demonstrate the feasibility of our framework in high-throughput biological analysis by revising a recent quantitative characterization of bone marrow vasculature in 3D confocal microscopy datasets. Not only can our work substantially ameliorate the use of deep learning in fluorescence microscopy analysis, but it can also be utilized in other fields with incomplete data acquisitions and missing modalities.Comment: 17 pages, 5 figures, 3 pages supplement (3 figures

The AIFELL Score as a Predictor of Coronavirus Disease 2019 (COVID-19) Severity and Progression in Hospitalized Patients

Since the beginning of the COVID-19 pandemic, SARS-CoV-2 has caused a global burden for health care systems due to high morbidity and mortality rates, leading to caseloads that episodically surpass hospital resources. Due to different disease manifestations, the triage of patients at high risk for a poor outcome continues to be a major challenge for clinicians. The AIFELL score was developed as a simple decision instrument for emergency rooms to distinguish COVID-19 patients in severe disease stages from less severe COVID-19 and non-COVID-19 cases. In the present study, we aimed to evaluate the AIFELL score as a prediction tool for clinical deterioration and disease severity in hospitalized COVID-19 patients. During the second wave of the COVID-19 pandemic in Switzerland, we analyzed consecutively hospitalized patients at the Triemli Hospital Zurich from the end of November 2020 until mid-February 2021. Statistical analyses were performed for group comparisons and to evaluate significance. AIFELL scores of patients developing severe COVID-19 stages IIb and III during hospitalization were significantly higher upon admission compared to those patients not surpassing stages I and IIa. Group comparisons indicated significantly different AIFELL scores between each stage. In conclusion, the AIFELL score at admission was useful to predict the disease severity and progression in hospitalized COVID-19 patients

Heterogeneity within AML with CEBPA mutations; only CEBPA double mutations, but not single CEBPA mutations are associated with favourable prognosis

CCAAT/enhancer binding protein alpha (CEBPA) mutations in AML are associated with favourable prognosis and are divided into N- and C-terminal mutations. The majority of AML patients have both types of mutations. We assessed the prognostic significance of single (n=7) and double (n=12) CEBPA mutations among 224 AML patients. Double CEBPA mutations conferred a decisively favourable overall (P=0.006) and disease-free survival (P=0.013). However, clinical outcome of patients with single CEBPA mutations was not different from CEBPA wild-type patients. In a multivariable analysis, only double – but not single – CEBPA mutations were identified as independent prognostic factors. These findings indicate heterogeneity within AML patients with CEBPA mutations