Deep brain stimulation (DBS) of the ventral internal capsule/ventral striatum (VCVS) is an emerging treatment for obsessive-compulsive disorder (OCD). Recently, multiple studies using normative connectomes have correlated DBS outcomes to stimulation of specific white matter tracts. Those studies did not test whether these correlations are clinically predictive, and did not apply cross-validation approaches that are necessary for biomarker development. Further, they did not account for the possibility of systematic differences between DBS patients and the non-diagnosed controls used in normative connectomes. To address these gaps, we performed patient-specific diffusion imaging in 8 patients who underwent VCVS DBS for OCD. We delineated tracts connecting thalamus and subthalamic nucleus (STN) to prefrontal cortex via VCVS. We then calculated which tracts were likely activated by individual patients' DBS settings. We fit multiple statistical models to predict both OCD and depression outcomes from tract activation. We further attempted to predict hypomania, a VCVS DBS complication. We assessed all models' performance on held-out test sets. With this best-practices approach, no model predicted OCD response, depression response, or hypomania above chance. Coefficient inspection partly supported prior reports, in that capture of tracts projecting to cingulate cortex was associated with both YBOCS and MADRS response. In contrast to prior reports, however, tracts connected to STN were not reliably correlated with response. Thus, patient-specific imaging and a guideline-adherent analysis were unable to identify a tractographic target with sufficient effect size to drive clinical decision-making or predict individual outcomes. These findings suggest caution in interpreting the results of normative connectome studies.
This paper presents results of measurements of selected gamma-radioactive radionuclide concentrations (7Be, 210Pb, 40K, 137Cs, 134Cs) in atmospheric aerosols registered in 2002-2017 at the Polish Polar Station of the Institute of Geophysics Polish Academy of Science in Hornsund and in the S. Kalinowski's Geophysical Observatory Institute of Geophysics Polish Academy of Science in Świder. The above measurements and tests are used to control and track long-term concentrations of radionuclides depending on the geometeorological conditions prevailing in the vicinity of the station. Collecting radiological data from polar regions and comparing them with data from medium latitudes leads to a better understanding of the mechanisms of creation and propagation of radionuclides in the air. Hornsund station is one of the northernmost measuring site for continuous airborne radionuclide monitoring in the Spitsbergen archipelago. It also allows the analysis of the relationship of radionuclides to the Earth's magnetic field.
BACKGROUND: Emerging data from longitudinal studies suggest that PRISm, defined by proportionate reductions in FEV1 and FVC, is a heterogeneous population with frequent transitions to other lung function categories relative to individuals with normal and obstructive spirometry. Controversy regarding the clinical significance of these transitions exists (e.g., whether transitions merely reflect measurement variability or "noise"). RESEARCH QUESTION: Are individuals with PRISm enriched for transitions associated with substantial changes in lung function? STUDY DESIGN AND METHODS: Current and former smokers enrolled in COPDGene with spirometry available at Phases 1-3 (enrollment, 5-year, and 10-year follow-up) were analyzed. Post-bronchodilator lung function categories were: PRISm=FEV1<80% predicted with FEV1/FVC ratio≥0.7, GOLD0=FEV1≥80% predicted and FEV1/FVC ≥0.7, and obstruction=FEV1/FVC<0.7. "Significant-transition" status was affirmative if a subject belonged to ≥2 spirometric categories and had >10% change in FEV1% and/or FVC% predicted between consecutive visits. "Ever-PRISm" was present if a subject had PRISm at any visit. Logistic regression examined the association between "significant-transitions" and "ever-PRISm" status, adjusted for age, sex, race, FEV1% predicted, current smoking, pack-years, BMI, and ever-positive bronchodilator response. RESULTS: Among subjects with complete data (n=1,775) over 10.1±0.4 years of follow-up, the prevalence of PRISm remained consistent (10.4%-11.3%) between P1-P3, but nearly half of subjects with PRISm transitioned into or out of PRISm at each visit. 19.7% of subjects had a "significant transition"; "ever-PRISm" was a significant predictor of "significant transitions" (ORunadjusted=10.3, 95%CI=7.9-13.5, ORadjusted=14.9, 95%CI=10.9-20.7). Results were similar with additional adjustment for radiographic emphysema and gas trapping, when lower limit of normal criteria were used to define lung function categories, and when FEV1 alone (regardless of change in FVC%) was used to define "significant transitions" . INTERPRETATION: PRISm is an unstable group, with frequent significant transitions to both obstruction and normal spirometry over time.
Delayed gadolinium-enhanced cardiac magnetic resonance (LGE-CMR) imaging requires novel and time-efficient approaches to characterize the myocardial substrate associated with ventricular arrhythmia in patients with ischemic cardiomyopathy. Using a translational approach in pigs and patients with established myocardial infarction, we tested and validated a novel 3D methodology to assess ventricular scar using custom transmural criteria and a semiautomatic approach to obtain transmural scar maps in ventricular models reconstructed from both 3D-acquired and 3D-upsampled-2D-acquired LGE-CMR images. The results showed that 3D-upsampled models from 2D LGE-CMR images provided a time-efficient alternative to 3D-acquired sequences to assess the myocardial substrate associated with ischemic cardiomyopathy. Scar assessment from 2D-LGE-CMR sequences using 3D-upsampled models was superior to conventional 2D assessment to identify scar sizes associated with the cycle length of spontaneous ventricular tachycardia episodes and long-term ventricular tachycardia recurrences after catheter ablation. This novel methodology may represent an efficient approach in clinical practice after manual or automatic segmentation of myocardial borders in a small number of conventional 2D LGE-CMR slices and automatic scar detection.
The polymeric title compound, [Cu2Br2(C4H8S)2] n , CP1, represents an example of a two-dimensional coordination polymer resulting from reaction of CuBr with tetra-hydro-thio-phene (THT) in MeCN solution. The two-dimensional layers consist of two different types of rhomboid-shaped dinuclear Cu(μ2-Br)2Cu secondary building units (SBUs); one with a quite loose Cu⋯Cu separation of 3.3348 (10) Å and a second one with a much closer inter-metallic contact of 2.9044 (9) Å. These SBUs are inter-connected through bridging THT ligands, in which the S atom acts as a four-electron donor bridging each Cu(μ2-Br)2Cu unit in a μ2-bonding mode. In the crystal, the layers are linked by very weak C-H⋯·Br hydrogen bonds with H⋯Br distances of 2.95 Å, thus giving rise to a three-dimensional supra-molecular network.
BACKGROUND: In acute pulmonary embolism, chest computed tomography angiography derived metrics, such as the right ventricle (RV): left ventricle ratio are routinely used for risk stratification. Paucity of intraparenchymal blood vessels has previously been described, but their association with clinical biomarkers and outcomes has not been studied. We sought to determine if small vascular volumes measured on computed tomography scans were associated with an abnormal RV on echocardiography and mortality. We hypothesized that decreased small venous volume would be associated with greater RV dysfunction and increased mortality.
METHODS: A retrospective cohort of patients with intermediate risk pulmonary embolism admitted to Brigham and Women's Hospital between 2009 and 2017 was assembled, and clinical and radiographic data were obtained. We performed 3-dimensional reconstructions of vasculature to assess intraparenchymal vascular volumes. Statistical analyses were performed using multivariable regression and cox proportional hazards models, adjusting for age, sex, lung volume, and small arterial volume.
RESULTS: Seven hundred twenty-two subjects were identified of whom 573 had documented echocardiography. A 50% reduction in small venous volume was associated with an increased risk of RV dilation (relative risk: 1.38 [95% CI, 1.18-1.63], P<0.001), RV dysfunction (relative risk: 1.62 [95% CI, 1.36-1.95], P<0.001), and RV strain (relative risk: 1.67 [95% CI, 1.37-2.04], P<0.001); increased cardiac biomarkers, and higher 30-day and 90-day mortality (hazard ratio: 2.50 [95% CI, 1.33-4.67], P=0.004 and hazard ratio: 1.84 [95% CI, 1.11-3.04], P=0.019, respectively).
CONCLUSIONS: Loss of small venous volume quantified from computed tomography angiography is associated with increased risk of abnormal RV on echocardiography, abnormal cardiac biomarkers, and higher risk of 30- and 90-day mortality. Small venous volume may be a useful marker for assessing disease severity in acute pulmonary embolism.
Specific features of white matter microstructure can be investigated by using biophysical models to interpret relaxation-diffusion MRI brain data. Although more intricate models have the potential to reveal more details of the tissue, they also incur time-consuming parameter estimation that may converge to inaccurate solutions due to a prevalence of local minima in a degenerate fitting landscape. Machine-learning fitting algorithms have been proposed to accelerate the parameter estimation and increase the robustness of the attained estimates. So far, learning-based fitting approaches have been restricted to microstructural models with a reduced number of independent model parameters where dense sets of training data are easy to generate. Moreover, the degree to which machine learning can alleviate the degeneracy problem is poorly understood. For conventional least-squares solvers, it has been shown that degeneracy can be avoided by acquisition with optimized relaxation-diffusion-correlation protocols that include tensor-valued diffusion encoding. Whether machine-learning techniques can offset these acquisition requirements remains to be tested. In this work, we employ artificial neural networks to vastly accelerate the parameter estimation for a recently introduced relaxation-diffusion model of white matter microstructure. We also develop strategies for assessing the accuracy and sensitivity of function fitting networks and use those strategies to explore the impact of the acquisition protocol. The developed learning-based fitting pipelines were tested on relaxation-diffusion data acquired with optimal and sub-optimal acquisition protocols. Networks trained with an optimized protocol were observed to provide accurate parameter estimates within short computational times. Comparing neural networks and least-squares solvers, we found the performance of the former to be less affected by sub-optimal protocols; however, model fitting networks were still susceptible to degeneracy issues and their use could not fully replace a careful design of the acquisition protocol.
BACKGROUND AND PURPOSE: Treatment of elevated intracranial pressure (ICP) is central to neurocritical care, but not all patients are eligible for invasive ICP-monitoring. A promising noninvasive option is ultrasound measurement of the optic nerve sheath diameter (ONSD). However, meta-analyses of ONSD for elevated ICP show wide confidence intervals. This might be due to baseline variations, inter-rater variability, and varying measurement methods. No standardized protocol has been validated. Corrections for eyeball diameter (ED) and optic nerve diameter (OND) may compensate for baseline variations. We evaluated a protocol and compared two different measurement methods for ONSD ultrasound. METHODS: Two operators, blinded to each other's measurements, measured ONSD, ED, and OND twice in 20 patients. ONSD was measured with two different methods in use: internal (ONSDint) or external (ONSDext) of the dura mater. Intra-class correlation (ICC) was calculated for inter-rater and intra-rater reliability. RESULTS: ICCs for inter-rater reliability of ONSDext and ONSDint (95% confidence interval) were 0.96 (0.93, 0.98) and 0.88 (0.79, 0.94), respectively. ICCs for intra-rater reliability of ONSDext and ONSDint were 0.97 (0.94, 0.99) and 0.93 (0.87, 0.96), respectively. There was no significant bias or difference in intra-rater reliability between operators. CONCLUSIONS: ONSD can be measured with an excellent inter- and intra-rater reliability and low risk of inter-rater bias, when using this protocol. ONSDext yields a higher inter- and intra-rater reliability than ONSDint. Corrections for ED and OND can be performed reliably.
Repetitive head impacts (RHI) are common in youth athletes participating in contact sports. RHI differ from concussions; they are considered hits to the head that usually do not result in acute symptoms and are therefore also referred to as "subconcussive" head impacts. RHI occur e.g., when heading the ball or during contact with another player. Evidence suggests that exposure to RHI may have cumulative effects on brain structure and function. However, little is known about brain alterations associated with RHI, or about the risk factors that may lead to clinical or behavioral sequelae. REPIMPACT is a prospective longitudinal study of competitive youth soccer players and non-contact sport controls aged 14 to 16 years. The study aims to characterize consequences of exposure to RHI with regard to behavior (i.e., cognition, and motor function), clinical sequelae (i.e., psychiatric and neurological symptoms), brain structure, function, diffusion and biochemistry, as well as blood- and saliva-derived measures of molecular processes associated with exposure to RHI (e.g., circulating microRNAs, neuroproteins and cytokines). Here we present the structure of the REPIMPACT Consortium which consists of six teams of clinicians and scientists in six countries. We further provide detailed information on the specific aims and the design of the REPIMPACT study. The manuscript also describes the progress made in the study thus far. Finally, we discuss important challenges and approaches taken to overcome these challenges.
PURPOSE: To provide a methodology that removes the spatial variability of in-plane resolution by using different CT reconstructions. The methodology does not require any training, sinogram or specific reconstruction method. METHODS: The methodology is formulated as a reconstruction problem. The desired sharp image is modeled as an unobservable variable to be estimated from an arbitrary number of observations with spatially variant resolution. The methodology comprises three steps: 1) Density harmonization, which removes the density variability across reconstructions. 2) PSF estimation, which estimates a spatially variant PSF with arbitrary shape. 3) Deconvolution, which is formulated as a regularized least squares problem. The assessment was performed with CT scans of phantoms acquired with three different Siemens scanners (Definition AS, Definition AS+, Drive). Four low-dose (LD) acquisitions reconstructed with backprojection and iterative methods were used for the resolution harmonization. A sharp, high-dose (HD) reconstruction was used as a validation reference. The different factors affecting the in-plane resolution (radial, angular, and longitudinal) were studied with regression analysis of the edge decay (between 10 and 90 percent of the edge spread function (ESF) amplitude). RESULTS: Results showed that the in-plane resolution improves remarkably and the spatial variability is substantially reduced without compromising the noise characteristics. The modulated transfer function (MTF) also confirmed a pronounced increase in resolution. The resolution improvement was also tested by measuring the wall thickness of tubes simulating airways. In all scanners, the resolution harmonization obtained better performance than the HD, sharp reconstruction used as a reference (up to 50 percent points). The methodology was also evaluated in clinical scans achieving a noise reduction and a clear improvement in thin-layered structures. The estimated ESF and MTF confirmed the resolution improvement. CONCLUSION: We propose a versatile methodology to reduce the spatial variability of in-plane resolution in CT scans by leveraging different reconstructions available in clinical studies. The methodology does not require any sinogram, training or specific reconstruction, and it is not limited to a fixed number of input images. Therefore, it can be easily adopted in multicenter studies and clinical practice. The results obtained with our resolution harmonization methodology evidence its suitability to reduce the spatially variant in-plane resolution in clinical CT scans without compromising the reconstruction's noise characteristics. We believe that the resolution increase achieved by our methodology may contribute in more accurate and reliable measurements of small structures such as vasculature, airways and wall thickness.
Background: CT screening for lung cancer results in a significant mortality reduction but is complicated by invasive procedures performed for evaluation of the many detected benign nodules. The purpose of this study was to evaluate measures of nodule location within the lung as predictors of malignancy. Methods: We analyzed images and data from 3,483 participants in the National Lung Screening Trial (NLST). All nodules (4-20 mm) were characterized by 3D geospatial location using a Cartesian coordinate system and evaluated in logistic regression analysis. Model development and probability cutpoint selection was performed in the NLST testing set. The Geospatial test was then validated in the NLST testing set, and subsequently replicated in a new cohort of 147 participants from The Detection of Early Lung Cancer Among Military Personnel (DECAMP) Consortium. Results: The Geospatial Test, consisting of the superior-inferior distance (Z distance), nodule diameter, and radial distance (carina to nodule) performed well in both the NLST validation set (AUC 0.85) and the DECAMP replication cohort (AUC 0.75). A negative Geospatial Test resulted in a less than 2% risk of cancer across all nodule diameters. The Geospatial Test correctly reclassified 19.7% of indeterminate nodules with a diameter over 6mm as benign, while only incorrectly classifying 1% of cancerous nodules as benign. In contrast, the parsimonious Brock Model applied to the same group of nodules correctly reclassified 64.5% of indeterminate nodules as benign but resulted in misclassification of a cancer as benign in 18.2% of the cases. Applying the Geospatial test would result in reducing invasive procedures performed for benign lesions by 11.3% with a low rate of misclassification (1.3%). In contrast, the Brock model applied to the same group of patients results in decreasing invasive procedures for benign lesion by 39.0% but misclassifying 21.1% of cancers as benign. Conclusions: Utilizing information about geospatial location within the lung improves risk assessment for indeterminate lung nodules and may reduce unnecessary procedures. Trial Registration: NCT00047385, NCT01785342.
White matter bundle segmentation using diffusion MRI fiber tractography has become the method of choice to identify white matter fiber pathways in vivo in human brains. However, like other analyses of complex data, there is considerable variability in segmentation protocols and techniques. This can result in different reconstructions of the same intended white matter pathways, which directly affects tractography results, quantification, and interpretation. In this study, we aim to evaluate and quantify the variability that arises from different protocols for bundle segmentation. Through an open call to users of fiber tractography, including anatomists, clinicians, and algorithm developers, 42 independent teams were given processed sets of human whole-brain streamlines and asked to segment 14 white matter fascicles on six subjects. In total, we received 57 different bundle segmentation protocols, which enabled detailed volume-based and streamline-based analyses of agreement and disagreement among protocols for each fiber pathway. Results show that even when given the exact same sets of underlying streamlines, the variability across protocols for bundle segmentation is greater than all other sources of variability in the virtual dissection process, including variability within protocols and variability across subjects. In order to foster the use of tractography bundle dissection in routine clinical settings, and as a fundamental analytical tool, future endeavors must aim to resolve and reduce this heterogeneity. Although external validation is needed to verify the anatomical accuracy of bundle dissections, reducing heterogeneity is a step towards reproducible research and may be achieved through the use of standard nomenclature and definitions of white matter bundles and well-chosen constraints and decisions in the dissection process.
Microstructure imaging seeks to noninvasively measure and map microscopic tissue features by pairing mathematical modeling with tailored MRI protocols. This article reviews an emerging paradigm that has the potential to provide a more detailed assessment of tissue microstructure-combined diffusion-relaxometry imaging. Combined diffusion-relaxometry acquisitions vary multiple MR contrast encodings-such as b-value, gradient direction, inversion time, and echo time-in a multidimensional acquisition space. When paired with suitable analysis techniques, this enables quantification of correlations and coupling between multiple MR parameters-such as diffusivity, T 1 , T 2 , and T 2 ∗ . This opens the possibility of disentangling multiple tissue compartments (within voxels) that are indistinguishable with single-contrast scans, enabling a new generation of microstructural maps with improved biological sensitivity and specificity.
Microscopic diffusion anisotropy imaging using diffusion-weighted MRI and multidimensional diffusion encoding is a promising method for quantifying clinically and scientifically relevant microstructural properties of neural tissue. Several methods for estimating microscopic fractional anisotropy (µFA), a normalized measure of microscopic diffusion anisotropy, have been introduced but the differences between the methods have received little attention thus far. In this study, the accuracy and precision of µFA estimation using q-space trajectory encoding and different signal models were assessed using imaging experiments and simulations. Three healthy volunteers and a microfibre phantom were imaged with five non-zero b-values and gradient waveforms encoding linear and spherical b-tensors. Since the ground-truth µFA was unknown in the imaging experiments, Monte Carlo random walk simulations were performed using axon-mimicking fibres for which the ground truth was known. Furthermore, parameter bias due to time-dependent diffusion was quantified by repeating the simulations with tuned waveforms, which have similar power spectra, and with triple diffusion encoding, which, unlike q-space trajectory encoding, is not based on the assumption of time-independent diffusion. The truncated cumulant expansion of the powder-averaged signal, gamma-distributed diffusivities assumption, and q-space trajectory imaging, a generalization of the truncated cumulant expansion to individual signals, were used to estimate µFA. The gamma-distributed diffusivities assumption consistently resulted in greater µFA values than the second order cumulant expansion, 0.1 greater when averaged over the whole brain. In the simulations, the generalized cumulant expansion provided the most accurate estimates. Importantly, although time-dependent diffusion caused significant overestimation of µFA using all the studied methods, the simulations suggest that the resulting bias in µFA is less than 0.1 in human white matter.
BACKGROUND: Chronic traumatic encephalopathy (CTE) is a neurodegenerative disease that has been neuropathologically diagnosed in brain donors exposed to repetitive head impacts, including boxers and American football, soccer, ice hockey, and rugby players. CTE cannot yet be diagnosed during life. In December 2015, the National Institute of Neurological Disorders and Stroke awarded a seven-year grant (U01NS093334) to fund the "Diagnostics, Imaging, and Genetics Network for the Objective Study and Evaluation of Chronic Traumatic Encephalopathy (DIAGNOSE CTE) Research Project." The objectives of this multicenter project are to: develop in vivo fluid and neuroimaging biomarkers for CTE; characterize its clinical presentation; refine and validate clinical research diagnostic criteria (i.e., traumatic encephalopathy syndrome [TES]); examine repetitive head impact exposure, genetic, and other risk factors; and provide shared resources of anonymized data and biological samples to the research community. In this paper, we provide a detailed overview of the rationale, design, and methods for the DIAGNOSE CTE Research Project. METHODS: The targeted sample and sample size was 240 male participants, ages 45-74, including 120 former professional football players, 60 former collegiate football players, and 60 asymptomatic participants without a history of head trauma or participation in organized contact sports. Participants were evaluated at one of four U.S. sites and underwent the following baseline procedures: neurological and neuropsychological examinations; tau and amyloid positron emission tomography; magnetic resonance imaging and spectroscopy; lumbar puncture; blood and saliva collection; and standardized self-report measures of neuropsychiatric, cognitive, and daily functioning. Study partners completed similar informant-report measures. Follow-up evaluations were intended to be in-person and at 3 years post-baseline. Multidisciplinary diagnostic consensus conferences are held, and the reliability and validity of TES diagnostic criteria are examined. RESULTS: Participant enrollment and all baseline evaluations were completed in February 2020. Three-year follow-up evaluations began in October 2019. However, in-person evaluation ceased with the COVID-19 pandemic, and resumed as remote, 4-year follow-up evaluations (including telephone-, online-, and videoconference-based cognitive, neuropsychiatric, and neurologic examinations, as well as in-home blood draw) in February 2021. CONCLUSIONS: Findings from the DIAGNOSE CTE Research Project should facilitate detection and diagnosis of CTE during life, and thereby accelerate research on risk factors, mechanisms, epidemiology, treatment, and prevention of CTE. TRIAL REGISTRATION: NCT02798185.
OBJECTIVES: Overall outcomes for trauma patients have improved over time. However, mortality for postinjury sepsis has been reported to be unchanged. Estimate incidence of and risk factors for sepsis in ICU patients after major trauma and the association between sepsis, mortality, and clinical course.
DESIGN SETTING AND PATIENTS: ICU in a large urban trauma center in Sweden with a well-developed trauma system. Retrospective cohort study of trauma patients admitted to the ICU for more than 24 hours were included.
MEASUREMENTS AND MAIN RESULTS: Primary outcome measure was 30-day mortality. Secondary outcomes were 1-year mortality and impact on clinical course. In total, 722 patients with a median Injury Severity Score of 26 (interquartile range, 18-38) were included. Incidence of sepsis was 22%. Septic patients had a four-fold increase in length of stay and need for organ supportive therapy. The overall 30-day mortality rate was 9.3%. After exclusion of early trauma-related deaths in the first 48 hours, the 30-day mortality rate was 6.7%. There was an association between sepsis and this adjusted 30-day mortality (day 3 odds ratio, 2.1 [95% CI, 1.1-3.9]; day 4 odds ratio, 3.1 [95% CI, 1.5-6.1]; day 5 odds ratio, 3.0 [95% CI, 1.4-6.2]). Septic patients had a 1-year mortality of 17.7% (nonseptic 11.0%). Development of sepsis was independently associated with age, spine and chest injury, shock, red cell transfusion, and positive blood alcohol concentration at admission. The risk of sepsis increased, in a dose-dependent manner, with the number of transfusions.
CONCLUSIONS: Postinjury sepsis was associated with a complicated clinical course and with mortality after exclusion of early, trauma-related deaths.
Background: There have been reports of increasing azole resistance in Candida tropicalis, especially in the Asia-Pacific region. Here we report on the epidemiology and antifungal susceptibility of C. tropicalis causing invasive candidiasis in China, from a 9-year surveillance study.
Methods: From August 2009 to July 2018, C. tropicalis isolates (n = 3702) were collected from 87 hospitals across China. Species identification was carried out by mass spectrometry or rDNA sequencing. Antifungal susceptibility was determined by Clinical and Laboratory Standards Institute disk diffusion (CHIF-NET10-14, n = 1510) or Sensititre YeastOne (CHIF-NET15-18, n = 2192) methods.
Results: Overall, 22.2% (823/3702) of the isolates were resistant to fluconazole, with 90.4% (744/823) being cross-resistant to voriconazole. In addition, 16.9 (370/2192) and 71.7% (1572/2192) of the isolates were of non-wild-type phenotype to itraconazole and posaconazole, respectively. Over the 9 years of surveillance, the fluconazole resistance rate continued to increase, rising from 5.7 (7/122) to 31.8% (236/741), while that for voriconazole was almost the same, rising from 5.7 (7/122) to 29.1% (216/741), with no significant statistical differences across the geographic regions. However, significant difference in fluconazole resistance rate was noted between isolates cultured from blood (27.2%, 489/1799) and those from non-blood (17.6%, 334/1903) specimens (P-value < 0.05), and amongst isolates collected from medical wards (28.1%, 312/1110) versus intensive care units (19.6%, 214/1092) and surgical wards (17.9%, 194/1086) (Bonferroni adjusted P-value < 0.05). Although echinocandin resistance remained low (0.8%, 18/2192) during the surveillance period, it was observed in most administrative regions, and one-third (6/18) of these isolates were simultaneously resistant to fluconazole.
Conclusion: The continual decrease in the rate of azole susceptibility among C. tropicalis strains has become a nationwide challenge in China, and the emergence of multi-drug resistance could pose further threats. These phenomena call for effective efforts in future interventions.
People learn new languages with varying degrees of success but what are the neuroanatomical correlates of the difference in language-learning aptitude? In this study, we set out to investigate how differences in cortical morphology and white matter microstructure correlate with aptitudes for vocabulary learning, phonetic memory, and grammatical inferencing as measured by the first-language neutral LLAMA test battery. We used ultra-high field (7T) magnetic resonance imaging to estimate the cortical thickness and surface area from sub-millimeter resolved image volumes. Further, diffusion kurtosis imaging was used to map diffusion properties related to the tissue microstructure from known language-related white matter tracts. We found a correlation between cortical surface area in the left posterior-inferior precuneus and vocabulary learning aptitude, possibly indicating a greater predisposition for storing word-figure associations. Moreover, we report negative correlations between scores for phonetic memory and axial kurtosis in left arcuate fasciculus as well as mean kurtosis, axial kurtosis, and radial kurtosis of the left superior longitudinal fasciculus III, which are tracts connecting cortical areas important for phonological working memory.