Observation of the Fractional Quantum Hall Effect in Graphene

When electrons are confined in two dimensions and subjected to strong magnetic fields, the Coulomb interactions between them become dominant and can lead to novel states of matter such as fractional quantum Hall liquids. In these liquids electrons linked to magnetic flux quanta form complex composite quasipartices, which are manifested in the quantization of the Hall conductivity as rational fractions of the conductance quantum. The recent experimental discovery of an anomalous integer quantum Hall effect in graphene has opened up a new avenue in the study of correlated 2D electronic systems, in which the interacting electron wavefunctions are those of massless chiral fermions. However, due to the prevailing disorder, graphene has thus far exhibited only weak signatures of correlated electron phenomena, despite concerted experimental efforts and intense theoretical interest. Here, we report the observation of the fractional quantum Hall effect in ultraclean suspended graphene, supporting the existence of strongly correlated electron states in the presence of a magnetic field. In addition, at low carrier density graphene becomes an insulator with an energy gap tunable by magnetic field. These newly discovered quantum states offer the opportunity to study a new state of matter of strongly correlated Dirac fermions in the presence of large magnetic fields

Validity of the Clock Drawing Test in predicting reports of driving problems in the elderly

BACKGROUND: This study examined the use of the Folstein Mini Mental Status Exam (MMSE) and the Clock Drawing Test (CDT) in predicting retrospective reports of driving problems among the elderly. The utility of existing scoring systems for the CDT was also examined. METHODS: Archival chart records of 325 patients of a geriatric outpatient clinic were reviewed, of which 162 had CDT results (including original clock drawings). T-test, correlation, and regression procedures were used to analyze the data. RESULTS: Both CDT and MMSE scores were significantly worse among non-drivers than individuals who were currently or recently driving. Among current or recent drivers, scores on both instruments correlated significantly with the total number of reported accidents or near misses, although the magnitude of the respective correlations was small. Only MMSE scores, however, significantly predicted whether or not any accidents or near misses were reported at all. Neither MMSE nor CDT scores predicted unique variance in the regressions. CONCLUSIONS: The overall results suggest that both the MMSE and CDT have limited utility as potential indicators of driving problems in the elderly. The demonstrated predictive power for these instruments appears to be redundant, such that both appear to assess general cognitive function versus more specific abilities. Furthermore, the lack of robust prediction suggests that neither are sufficient to serve as stand-alone instruments on which to solely base decisions of driving capacity. Rather, individuals who evidence impairment should be provided a more thorough and comprehensive assessment than can be obtained through screening tools

Validating the Time and Change test to screen for dementia in elderly Koreans

BACKGROUND: We assessed the applicability of the T&C test as an accurate and convenient means to screen for dementia in primary care and community settings. METHODS: The study group comprised 59 patients and 405 community participants, all of who were aged 65 years and over. The time component of the T&C test evaluated the ability of a subject to comprehend clock hands that indicated a time of 11:10, while the change component of the T&C test evaluated the ability of a subject to make 1,000 Won from a group of coins with smaller denominations (one 500, seven 100, and seven 50 Won coins). RESULTS: The T&C test had a sensitivity and specificity of 73.0 and 90.9%, respectively, and positive and negative predictive values of 93.1, and 66.7%, respectively. The test-retest and interobserver agreement rates were both 95% (κ = 0.91) (time interval, 24 hours). The association between the T&C test and K-MMSE test was modest, while significant (r = 0.422, p < 0.001). The T&C test scores were not influenced by educational status. CONCLUSIONS: We conclude that the T&C test is useful as supplemental testing of important domains (e.g., calculation, conceptualization, visuospatial) to traditional measures such as the MMSE. However, because T&C test is simple, rapid, and easy to use, it can be applied conveniently to elderly subjects by non-specialist personnel who receive training

Carbon Dioxide Embolism during Laparoscopic Surgery

Clinically significant carbon dioxide embolism is a rare but potentially fatal complication of anesthesia administered during laparoscopic surgery. Its most common cause is inadvertent injection of carbon dioxide into a large vein, artery or solid organ. This error usually occurs during or shortly after insufflation of carbon dioxide into the body cavity, but may result from direct intravascular insufflation of carbon dioxide during surgery. Clinical presentation of carbon dioxide embolism ranges from asymptomatic to neurologic injury, cardiovascular collapse or even death, which is dependent on the rate and volume of carbon dioxide entrapment and the patient's condition. We reviewed extensive literature regarding carbon dioxide embolism in detail and set out to describe the complication from background to treatment. We hope that the present work will improve our understanding of carbon dioxide embolism during laparoscopic surgery

Increased CSF levels of aromatic amino acids in hip fracture patients with delirium suggests higher monoaminergic activity

textabstractBackground: To examine whether delirium in hip fracture patients was associated with changes in the levels of amino acids and/or monoamine metabolites in cerebrospinal fluid (CSF) and serum. Methods: In this prospective cohort study, 77 patients admitted with an acute hip fracture to Oslo University Hospital, Norway, were studied. The concentrations of amino acids in CSF and serum were determined by high performance liquid chromatography. The patients were assessed daily for delirium by the Confusion Assessment Method (pre-operatively and post-operative day 1-5 (all) or until discharge (delirious patients)). Pre-fracture dementia status was decided by an expert panel. Serum was collected pre-operatively and CSF immediately before spinal anesthesia. Results: Fifty-three (71 %) hip fracture patients developed delirium. In hip fracture patients without dementia (n = 39), those with delirium had significantly higher CSF levels of tryptophan (40 % higher), tyrosine (60 % higher), phenylalanine (59 % higher) and the monoamine metabolite 5-hydroxyindoleacetate (23 % higher) compared to those without delirium. The same amino acids were also higher in CSF in delirious patients with dementia (n = 38). The correlations between serum and CSF amino acid levels were poor. Conclusion: Higher CSF levels of monoamine precursors in hip fracture patients with delirium suggest a higher monoaminergic activity in the central nervous system during delirium in this patient group

Prediction of hot spot residues at protein-protein interfaces by combining machine learning and energy-based methods

Background: Alanine scanning mutagenesis is a powerful experimental methodology for investigating the structural and energetic characteristics of protein complexes. Individual aminoacids are systematically mutated to alanine and changes in free energy of binding (Delta Delta G) measured. Several experiments have shown that protein-protein interactions are critically dependent on just a few residues ("hot spots") at the interface. Hot spots make a dominant contribution to the free energy of binding and if mutated they can disrupt the interaction. As mutagenesis studies require significant experimental efforts, there is a need for accurate and reliable computational methods. Such methods would also add to our understanding of the determinants of affinity and specificity in protein-protein recognition.Results: We present a novel computational strategy to identify hot spot residues, given the structure of a complex. We consider the basic energetic terms that contribute to hot spot interactions, i.e. van der Waals potentials, solvation energy, hydrogen bonds and Coulomb electrostatics. We treat them as input features and use machine learning algorithms such as Support Vector Machines and Gaussian Processes to optimally combine and integrate them, based on a set of training examples of alanine mutations. We show that our approach is effective in predicting hot spots and it compares favourably to other available methods. In particular we find the best performances using Transductive Support Vector Machines, a semi-supervised learning scheme. When hot spots are defined as those residues for which Delta Delta G >= 2 kcal/mol, our method achieves a precision and a recall respectively of 56% and 65%.Conclusion: We have developed an hybrid scheme in which energy terms are used as input features of machine learning models. This strategy combines the strengths of machine learning and energy-based methods. Although so far these two types of approaches have mainly been applied separately to biomolecular problems, the results of our investigation indicate that there are substantial benefits to be gained by their integration