Deep neck space infections: comparison of outcomes between diabetic and non-diabetic patients

Background: The objective of the study was to study the clinical presentation, microbiological profile, treatment protocol of deep neck space infections in diabetics and non diabetics.Methods: This was a prospective study conducted on 76 patients (diabetics and non diabetics) admitted in the Department of Otorhinolaryngology, TD Medical college, Alappuzha over a period of 18 months from January 2012 to June 2013.Results: The age distribution was 15-75 years. Male to female ratio was 2:1. Fever, pain, neck swelling and odynophagia were the common symptoms with dyspnoea and chest pain indicative of complications. The most common etiology was odontogenic (68.4%) followed by tonsillopharyngeal infection and foreign bodies. No etiological factor was found in 34.2%. The commonest site was submandibular space (64.2%) followed by parapharyngeal space (26.6%). Abscess was present in majority needing surgical drainage. The most common organism isolated was streptococcus viridans (37.5%). Preponderance of klebsiella species was noted in diabetics. Streptococcus showed susceptibility to pencillin (83.33%), ampicillin (92%), cefotaxime (60.526%). Klebsiella showed susceptibility to gentamicin (42.3%) and ciprofloxacin (28.57%). The complication rate was more in diabetics (34.21%). Contrast enhanced CT was done in cases suspected to have complication. The mean hospital stay was longer in diabetics (19.6 days) than non diabetics (6.4 days).Conclusions: Deep neck space infection still remains life threatening if not heeded promptly. Senescence and diabetes demand surgical intervention and meticulous glycemic control to prevent complications. Judicious use of antimicrobials and timely radiological and surgical interventions have come a long way in the management and in providing a cure to this dreaded condition

Conditions where random phase approximation becomes exact in the high-density limit

It is shown that, in d-dimensional systems, the vertex corrections beyond the random phase approximation (RPA) or GW approximation scales with the power d - beta - alpha of the Fermi momentum if the relation between Fermi energy and Fermi momentum is epsilon(f) similar to p(f)(beta) and the interacting potential possesses a momentum power law of similar to p(-alpha). The condition d - beta - alpha < 0 specifies systems where RPA is exact in the high-density limit. The one-dimensional structure factor is found to be the interaction-free one in the high-density limit for contact interaction. A cancellation of RPA and vertex corrections render this result valid up to second order in contact interaction. For finite-range potentials of cylindrical wires a large-scale cancellation appears and is found to be independent of the width parameter of the wire. The proposed high-density expansion agrees with the quantum Monte Carlo simulations

Chargeâ Transport Properties of F6TNAPâ Based Chargeâ Transfer Cocrystals

The crystal structures of the chargeâ transfer (CT) cocrystals formed by the Ï â electron acceptor 1,3,4,5,7,8â hexafluoroâ 11,11,12,12â tetracyanonaphthoâ 2,6â quinodimethane (F6TNAP) with the planar Ï â electronâ donor molecules triphenylene (TP), benzo[b]benzo[4,5]thieno[2,3â d]thiophene (BTBT), benzo[1,2â b:4,5â bâ ²]dithiophene (BDT), pyrene (PY), anthracene (ANT), and carbazole (CBZ) have been determined using singleâ crystal Xâ ray diffraction (SCXRD), along with those of two polymorphs of F6TNAP. All six cocrystals exhibit 1:1 donor/acceptor stoichiometry and adopt mixedâ stacking motifs. Cocrystals based on BTBT and CBZ Ï â electron donor molecules exhibit brickwork packing, while the other four CT cocrystals show herringboneâ type crystal packing. Infrared spectroscopy, molecular geometries determined by SCXRD, and electronic structure calculations indicate that the extent of groundâ state CT in each cocrystal is small. Density functional theory calculations predict large conduction bandwidths and, consequently, low effective masses for electrons for all six CT cocrystals, while the TPâ , BDTâ , and PYâ based cocrystals are also predicted to have large valence bandwidths and low effective masses for holes. Chargeâ carrier mobility values are obtained from spaceâ charge limited current (SCLC) measurements and fieldâ effect transistor measurements, with values exceeding 1 cm2 Vâ 1 s1 being estimated from SCLC measurements for BTBT:F6TNAP and CBZ:F6TNAP cocrystals.Structural, electronic band structure, and electrical properties of a series of chargeâ transfer cocrystals based on F6TNAP and six planar donors are presented. Density functional theory calculations afford large conduction bandwidths and low effective masses for all six cocrystals. A few cocrystals exhibit chargeâ carrier mobilities in excess of 1 cm2 Vâ 1 sâ 1, as estimated from spaceâ charge limited current measurements.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/153248/1/adfm201904858-sup-0001-S1.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/153248/2/adfm201904858.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/153248/3/adfm201904858_am.pd

Population differentiation of Southern Indian male lineages correlates with agricultural expansions predating the caste system

Christina J. Adler, Alan Cooper, Clio S.I. Der Sarkissian and Wolfgang Haak are contributors to the Genographic ConsortiumPrevious studies that pooled Indian populations from a wide variety of geographical locations, have obtained contradictory conclusions about the processes of the establishment of the Varna caste system and its genetic impact on the origins and demographic histories of Indian populations. To further investigate these questions we took advantage that both Y chromosome and caste designation are paternally inherited, and genotyped 1,680 Y chromosomes representing 12 tribal and 19 non-tribal (caste) endogamous populations from the predominantly Dravidian-speaking Tamil Nadu state in the southernmost part of India. Tribes and castes were both characterized by an overwhelming proportion of putatively Indian autochthonous Y-chromosomal haplogroups (H-M69, F-M89, R1a1-M17, L1-M27, R2-M124, and C5-M356; 81% combined) with a shared genetic heritage dating back to the late Pleistocene (10–30 Kya), suggesting that more recent Holocene migrations from western Eurasia contributed, <20% of the male lineages. We found strong evidence for genetic structure, associated primarily with the current mode of subsistence. Coalescence analysis suggested that the social stratification was established 4–6 Kya and there was little admixture during the last 3 Kya, implying a minimal genetic impact of the Varna(caste) system from the historically-documented Brahmin migrations into the area. In contrast, the overall Y-chromosomal patterns, the time depth of population diversifications and the period of differentiation were best explained by the emergence of agricultural technology in South Asia. These results highlight the utility of detailed local genetic studies within India, without prior assumptions about the importance of Varna rank status for population grouping, to obtain new insights into the relative influences of past demographic events for the population structure of the whole of modern India.GaneshPrasad ArunKumar, David F. Soria-Hernanz, Valampuri John Kavitha, Varatharajan Santhakumari Arun, Adhikarla Syama, Kumaran Samy Ashokan, Kavandanpatti Thangaraj Gandhirajan, Koothapuli Vijayakumar, Muthuswamy Narayanan, Mariakuttikan Jayalakshmi, Janet S. Ziegle, Ajay K. Royyuru, Laxmi Parida, R. Spencer Wells, Colin Renfrew, Theodore G. Schurr, Chris Tyler Smith, Daniel E. Platt, Ramasamy Pitchappan, The Genographic Consortiu

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation