Socio-economic factors Influencing Infant and Child Mortality among the Zou of Manipur

The present study was conducted to find out the influence ofsocio-economic factors on infant and child mortality among the Zou,a tribal population of Manipur. A cross-sectional study was executedamong 533 mothers of age 17- 49 years following house to housevisits from December 2016 to February 2017. The finding showsthere is a significant correlation of the educational level of themother, household income, child immunization to that of infant andchild mortality in the study population

Incumbent audit firm-provided tax services and the clients with low financial reporting quality

This study investigates whether incumbent audit firm-provided tax services enhance or impair the likelihood of acknowledging client companies' low financial reporting quality. In particular, we examine the association between tax-related fees and the likelihood of timely restatements, and internal control weakness disclosures among a sample of US companies that all have misstatements in financial information. The empirical findings indicate that companies paying higher tax-related fees are less likely to disclose SOX 404 internal control weakness disclosures, implying that underlying control problems are unacknowledged when incumbent audit firm provided tax-related fees are higher. However, the findings suggest that just providing both audit and tax-related services does not have an impact on audit quality per se, but rather it is the magnitude of the tax-related fees in particular that counts. We also find some evidence suggesting that companies paying higher tax-related fees have higher likelihood of restatement lags, whereas companies paying smaller tax-related fees to their audit firm restate financial statements in a timelier manner. Overall, the findings suggest that audit scrutiny of client companies with low quality financial reporting is weaker when the magnitude of tax-related fees is higher

Topological modes bound to dislocations in mechanical metamaterials

Mechanical metamaterials are artificial structures with unusual properties, such as negative Poisson ratio, bistability or tunable vibrational properties, that originate in the geometry of their unit cell. At the heart of such unusual behaviour is often a soft mode: a motion that does not significantly stretch or compress the links between constituent elements. When activated by motors or external fields, soft modes become the building blocks of robots and smart materials. Here, we demonstrate the existence of topological soft modes that can be positioned at desired locations in a metamaterial while being robust against a wide range of structural deformations or changes in material parameters. These protected modes, localized at dislocations, are the mechanical analogue of topological states bound to defects in electronic systems. We create physical realizations of the topological modes in prototypes of kagome lattices built out of rigid triangular plates. We show mathematically that they originate from the interplay between two Berry phases: the Burgers vector of the dislocation and the topological polarization of the lattice. Our work paves the way towards engineering topologically protected nano-mechanical structures for molecular robotics or information storage and read-out.Comment: 13 pages, 6 figures; changes to text and figures and added analysis on mode localization; see http://www.lorentz.leidenuniv.nl/~paulose/dislocation-modes/ for accompanying video

Flux-Enabled Exploration of the Role of Sip1 in galactose yeast metabolism

13C metabolic flux analysis (13C MFA) is an important systems biology technique that has been used to investigate microbial metabolism for decades. The heterotrimer Snf1 kinase complex plays a key role in the preference Saccharomyces cerevisiae exhibits for glucose over galactose, a phenomenon known as glucose repression or carbon catabolite repression. The SIP1 gene, encoding a part of this complex, has received little attention, presumably, because its knockout lacks a growth phenotype. We present a fluxomic investigation of the relative effects of the presence of galactose in classically glucose-repressing media and/or knockout of SIP1 using a multi-scale variant of 13C MFA known as 2-Scale 13C metabolic flux analysis (2S-13C MFA). In this study, all strains have the galactose metabolism deactivated (gal1Δ background) so as to be able to separate the metabolic effects purely related to glucose repression from those arising from galactose metabolism. The resulting flux profiles reveal that the presence of galactose in classically glucose-repressing conditions, for a CEN.PK113-7D gal1Δ background, results in a substantial decrease in pentose phosphate pathway (PPP) flux and increased flow from cytosolic pyruvate and malate through the mitochondria toward cytosolic branched-chain amino acid biosynthesis. These fluxomic redistributions are accompanied by a higher maximum specific growth rate, both seemingly in violation of glucose repression. Deletion of SIP1 in the CEN.PK113-7D gal1Δ cells grown in mixed glucose/galactose medium results in a further increase. Knockout of this gene in cells grown in glucose-only medium results in no change in growth rate and a corresponding decrease in glucose and ethanol exchange fluxes and flux through pathways involved in aspartate/threonine biosynthesis. Glucose repression appears to be violated at a 1/10 ratio of galactose-to-glucose. Based on the scientific literature, we may have conducted our experiments near a critical sugar ratio that is known to allow galactose to enter the cell. Additionally, we report a number of fluxomic changes associated with these growth rate increases and unexpected flux profile redistributions resulting from deletion of SIP1 in glucose-only medium

Using the relationship between brain tissue regional saturation of oxygen and mean arterial pressure to determine the optimal mean arterial pressure in patients following cardiac arrest: A pilot proof-of-concept study.

INTRODUCTION: Prospectively assess cerebral autoregulation and optimal mean arterial pressure (MAPOPT) using the dynamic relationship between MAP and regional saturation of oxygen (rSO2) using near-infrared spectroscopy. METHODS: Feasibility study of twenty patients admitted to the intensive care unit following a cardiac arrest. All patients underwent continuous rSO2 monitoring using the INVOS(®) cerebral oximeter. ICM+(®) brain monitoring software calculates the cerebral oximetry index (COx) in real-time which is a moving Pearson correlation coefficient between 30 consecutive, 10-s averaged values of MAP and correspond rSO2 signals. When rSO2 increases with increasing MAP (COx ≥0.3), cerebral autoregulation is dysfunctional. Conversely, when rSO2 remains constant or decreases with increasing MAP (COx <0.3), autoregulation is preserved. ICM+(®) fits a U-shaped curve through the COx values plotted vs. MAP. The MAPOPT is nadir of this curve. RESULTS: The median age was 59 years (IQR 54-67) and 7 of 20 were female. The cardiac arrest was caused by myocardial infarction in 12 (60%) patients. Nineteen arrests were witnessed and return of spontaneous circulation occurred in a median of 15.5min (IQR 8-33). Patients underwent a median of 30h (IQR 23-46) of monitoring. COx curves and MAPOPT were generated in all patients. The mean overall MAP and MAPOPT were 76mmHg (SD 10) and 76mmHg (SD 7), respectively. MAP was outside of 5mmHg from MAPOPT in 50% (SD 15) of the time. Out of the 7672 5-min averaged COx measurements, 1182 (15%) were at 0.3 or above, indicating absence of autoregulation. Multivariable polynomial fractional regression demonstrated an increase in COx with increasing temperature (P=0.008). CONCLUSIONS: We demonstrated the feasibility to determine a MAPOPT using cerebral oximetry in patients after cardiac arrest

Lessons from Two Design–Build–Test–Learn Cycles of Dodecanol Production in Escherichia coli Aided by Machine Learning

The Design–Build–Test–Learn (DBTL) cycle, facilitated by exponentially improving capabilities in synthetic biology, is an increasingly adopted metabolic engineering framework that represents a more systematic and efficient approach to strain development than historical efforts in biofuels and biobased products. Here, we report on implementation of two DBTL cycles to optimize 1-dodecanol production from glucose using 60 engineered Escherichia coli MG1655 strains. The first DBTL cycle employed a simple strategy to learn efficiently from a relatively small number of strains (36), wherein only the choice of ribosome-binding sites and an acyl-ACP/acyl-CoA reductase were modulated in a single pathway operon including genes encoding a thioesterase (UcFatB1), an acyl-ACP/acyl-CoA reductase (Maqu_2507, Maqu_2220, or Acr1), and an acyl-CoA synthetase (FadD). Measured variables included concentrations of dodecanol and all proteins in the engineered pathway. We used the data produced in the first DBTL cycle to train several machine-learning algorithms and to suggest protein profiles for the second DBTL cycle that would increase production. These strategies resulted in a 21% increase in dodecanol titer in Cycle 2 (up to 0.83 g/L, which is more than 6-fold greater than previously reported batch values for minimal medium). Beyond specific lessons learned about optimizing dodecanol titer in E. coli, this study had findings of broader relevance across synthetic biology applications, such as the importance of sequencing checks on plasmids in production strains as well as in cloning strains, and the critical need for more accurate protein expression predictive tools