Lack of Increase in Intracranial Pressure After Epidural Blood Patch in Spinal Cerebrospinal Fluid Leak

Background and Importance: Epidural blood patch (EBP) is one therapeutic measure for patients suffering from spontaneous intracranial hypotension (SIH) or post-lumbar puncture headaches. It has been proposed that an EBP may directly seal a spinal cerebrospinal fluid (CSF) fistula or result in an increase in intracranial pressure (ICP) by a shift of CSF from the spinal to the intracranial compartment. To the best of our knowledge this is the first case of a patient with SIH and neurological deterioration in whom ICP was measured before, during, and after spinal EBP. Clinical Presentation: This 52-year old previously healthy man presented with holocephal headaches. MRI showed a left hemispheric subdural fluid collection causing a significant mass effect. Myelography revealed a CSF leak with epidural contrast at the left side of the L-2 level. To seal the CSF leak, we performed an EBP procedure targeted at left L-2 level and recorded ICP. After applying the epidural blood patch (15 cc) the patient improved rapidly, ICP however remained unchanged before, during, and after the procedure. One day post-treatment, he had a GCS score increase from 12 to 15 and no headache or neurological deficits. Conclusion: A shift of CSF from the spinal to the cranial compartment with a subsequent rise in ICP might not be a beneficial therapeutic mechanism of spinal epidural blood patchin

Clinical assessment of deficits after SAH: hasty neurosurgeons and accurate neurologists

For survivors of aneurysmal subarachnoid hemorrhage (SAH), somatic and cognitive deficits can affect long-term outcomes. We were interested in comparing the deficits identified in SAH patients, including cognitive deficits, at discharge by neurosurgeons and deficits identified by neurologists upon admission to the rehabilitation unit on the same day. The assessment of deficits might have an impact on referring patients to rehabilitation. This retrospective study included 494 SAH patients treated between 2005 and 2010. Of these, 50 patients were discharged to an affiliated rehabilitation unit. Deficits were grouped into 18 categories and summarized into three groups: major somatic, minor somatic, and cognitive deficits. Major somatic deficits were identified in 16 and 20 patients (p=0.53), minor somatic deficits in 16 and 44 (p<0.0001) patients, and cognitive deficits in 36 and 45 (p<0.04) patients by neurosurgeons and neurologists, respectively. The absolute number of deficits in daily activities identified by the neurosurgeon and neurologist were 21 and 31 major somatic deficits (p=0.2), 18 and 97 minor somatic deficits (p<0.0001), and 61 and 147 cognitive deficits (p<0.0001), respectively. Significant differences in assessment of cognitive and minor somatic deficits between neurosurgeons and neurologists exist. Based on these findings, it is evident that for the neurosurgeon, there needs to be an increased awareness of the assessment of cognitive deficits and a more routine interdisciplinary approach, including the use of neuropsychological evaluations, to ensure a better triage of patients to rehabilitation or for discharge hom

Pengaruh Brand Satisfaction, Brand Image, Brand Impact Terhadap Brand Loyalty Pada PT. Kopin

Tujuan dari penelitian ini adalah untuk menganalisa dan menguji pengaruh brand satisfaction, brand image, brand impactter hadap brand loyalty pada PT Kopin. Bentuk penelitian yang dilakukan pada penelitian ini ialah deskriptif dan kausalitas dengan menggunakan lima poin skala likert untuk mengukur seluruh variabel. Pengambilan sampel menggunakan teknik purposive sampling dengan data primer dan sekunder dan jumlah responden sebanyak 108 responden. Metode analisis data yang digunakan dalam penelitian ini ialah regresi linear berganda dengan alat uji IBM SPSS statistic 25. Hasil penelitian ini menunjukkan bahwa brand satisfaction, brand image, brand impact memiliki pengaruh terhadap brand loyalty pada pelanggan PT Kopin, hal ini di tunjukan dengan anova dan uji parsial maupun simultan yang signifikan

Engineered K1F bacteriophages kill intracellular Escherichia coli K1 in human epithelial cells

Bacterial infections can be treated with bacteriophages that show great specificity towards their bacterial host and can be genetically modified for different applications. However, whether and how bacteriophages can kill intracellular bacteria in human cells remains elusive. Here, using CRISPR/Cas selection, we have engineered a fluorescent bacteriophage specific for E. coli K1, a nosocomial pathogen responsible for urinary tract infections, neonatal meningitis and sepsis. By confocal and live microscopy, we show that engineered bacteriophages K1F-GFP and E. coli EV36-RFP bacteria displaying the K1 capsule, enter human cells via phagocytosis. Importantly, we show that bacteriophage K1F-GFP efficiently kills intracellular E. coli EV36-RFP in T24 human urinary bladder epithelial cells. Finally, we provide evidence that bacteria and bacteriophages are degraded by LC3-associated phagocytosis and xenophagy

Traumatic subarachnoid hemorrhage, basal ganglia hematoma and ischemic stroke caused by a torn lenticulostriate artery

Subarachnoid hemorrhage (SAH), basal ganglia hematoma (BGH) and ischemic stroke are common diseases with diverging therapies. The simultaneous occurrence of these diseases is rare and complicates the therapy. We report the case of a 30-year-old man with a ruptured lenticulostriate artery after traumatic brain injury that caused the combination of SAH, BGH and ischemic stroke and subsequent cerebral vasospasm. This rupture mimicked the pathophysiology and imaging appearance of aneurysmal SAH. The site of rupture was not secured by any treatment; however, hyperdynamic therapy and percutaneous transluminal angioplasty were feasible in this setting to prevent additional delayed neurological defici

Outcome after surgical treatment of cerebrospinal fluid leaks in spontaneous intracranial hypotension-a matter of time.

OBJECTIVE Spinal cerebrospinal fluid (CSF) leaks cause spontaneous intracranial hypotension (SIH). Microsurgery can sufficiently seal spinal CSF leaks. Yet, some patients suffer from residual symptoms. Aim of the study was to assess predictors for favorable outcome after surgical treatment of SIH. METHODS We included consecutive patients with SIH treated surgically from January 2013 to May 2020. Subjects were surveyed by a questionnaire. Primary outcome was resolution of symptoms as rated by the patient. Secondary outcome was postoperative headache intensity on the numeric rating scale (NRS). Association between variables and outcome was assessed using univariate and multivariate regression. A cut-off value for continuous variables was calculated by a ROC analysis. RESULTS Sixty-nine out of 86 patients (80.2%) returned the questionnaire and were analyzed. Mean age was 46.7 years and 68.1% were female. A significant association with the primary and secondary outcome was found only for preoperative symptom duration (p = 0.001 and p < 0.001), whereby a shorter symptom duration was associated with a better outcome. Symptom duration remained a significant predictor in a multivariate model (p = 0.013). Neither sex, age, type of pathology, lumbar opening pressure, nor initial presentation were associated with the primary outcome. ROC analysis yielded treatment within 12 weeks as a cut-off for better outcome. CONCLUSION Shorter duration of preoperative symptoms is the most powerful predictor of favorable outcome after surgical treatment of SIH. While an initial attempt of conservative treatment is justified, we advocate early definitive treatment within 12 weeks in case of persisting symptoms

A Review of the Applications of Quantum Machine Learning in Optical Communication Systems

In the context of optical signal processing, quantum and quantum-inspired machine learning algorithms have massive potential for deployment. One of the applications is in error correction protocols for the received noisy signals. In some scenarios, non-linear and unknown errors can lead to noise that bypasses linear error correction protocols that optical receivers generally implement. In those cases, machine learning techniques are used to recover the transmitted signal from the received signal through various estimation procedures. Since quantum machine learning algorithms promise advantage over classical algorithms, we expect that optical signal processing can benefit from these advantages. In this review, we survey several proposed quantum and quantum-inspired machine learning algorithms and their applicability with current technology to optical signal processing.Comment: European Wireless Conference (EW) 2023 - 6G Driving a Sustainable Growt

Extreme events driving year-to-year differences in gross primary productivity across the US

Solar-Induced chlorophyll Fluorescence (SIF) has previously been shown to strongly correlate with gross primary productivity (GPP), however this relationship has not yet been quantified for the recently launched TROPOspheric Monitoring Instrument (TROPOMI). Here we use a Gaussian mixture model to develop a parsimonious relationship between SIF from TROPOMI and GPP from flux towers across the conterminous United States (CONUS). The mixture model indicates the SIF-GPP relationship can be characterized by a linear model with two terms. We then estimate GPP across CONUS at 500-m spatial resolution over a 16-day moving window. We find that CONUS GPP varies by less than 4% between 2018 and 2019. However, we observe four extreme precipitation events that induce regional GPP anomalies: drought in west Texas, flooding in the midwestern US, drought in South Dakota, and drought in California. Taken together, these events account for 28% of the year-to-year GPP differences across CONUS

Quantum and Quantum-Inspired Stereographic K Nearest-Neighbour Clustering

Nearest-neighbour clustering is a simple yet powerful machine learning algorithm that finds natural application in the decoding of signals in classical optical fibre communication systems. Quantum nearest-neighbour clustering promises a speed-up over the classical algorithms, but the current embedding of classical data introduces inaccuracies, insurmountable slowdowns, or undesired effects. This work proposes the generalised inverse stereographic projection into the Bloch sphere as an encoding for quantum distance estimation in k nearest-neighbour clustering, develops an analogous classical counterpart, and benchmarks its accuracy, runtime and convergence. Our proposed algorithm provides an improvement in both the accuracy and the convergence rate of the algorithm. We detail an experimental optic fibre setup as well, from which we collect 64-Quadrature Amplitude Modulation data. This is the dataset upon which the algorithms are benchmarked. Through experiments, we demonstrate the numerous benefits and practicality of using the `quantum-inspired' stereographic k nearest-neighbour for clustering real-world optical-fibre data. This work also proves that one can achieve a greater advantage by optimising the radius of the inverse stereographic projection.Comment: Submitted to Entrop