Magnetic resonance imaging of the knee anteromedial quadrant.

OBJECTIVE: This study aims to evaluate the possibility of characterizing an extra-articular thickening in the knee anteromedial quadrant in routine MRI scans. MATERIALS AND METHODS: Firstly, in a pilot study, for a better understanding of this extra-articular thickening trajectory in MRI, polytetrafluoroethylene (PTFE) tubes were attached to the ligament structure topography in two dissected pieces. Afterward, 100 knee MRI studies were randomly selected from our database, and 97 met the inclusion criteria. Two musculoskeletal radiologists interpreted the exams separately. Both had previously studied the ligament in the cadaveric knee MRI with the PTFE tube. RESULTS: The intraobserver and interobserver agreement for the ligament identification was calculated using Cohen's Kappa coefficient. The first radiologist identified the structure in 41 of the 97 scans (42.2%), and the second radiologist in 38 scans (39.2%). The interobserver agreement was substantial, with a Kappa of 0.68 and an agreement of 84.5%. The results suggest that this extra-articular thickening, recently called Anterior Oblique Ligament (AOL) in the literature, is a structure that can be frequently visualized on MRI scans with a high level of interobserver agreement in a relatively large number of exams. CONCLUSION: Therefore, this study indicates that MRI is a promising method for evaluating this anteromedial thickening, and it may be used for future studies of the Anterior Oblique Ligament.

Characterization of Functional Coatings on Cork Stoppers with Laser-Induced Breakdown Spectroscopy Imaging.

Evaluating the efficiency of surface treatments is a problem of paramount importance for the cork stopper industry. Generically, these treatments create coatings that aim to enhance the impermeability and lubrification of cork stoppers. Yet, current methods of surface analysis are typically time-consuming, destructive, have poor representativity or rely on indirect approaches. In this work, the use of a laser-induced breakdown spectroscopy (LIBS) imaging solution is explored for evaluating the presence of coating along the cylindrical surface and in depth. To test it, several cork stoppers with different shaped areas of untreated surface were analyzed by LIBS, making a rectangular grid of spots with multiple shots per spot, to try to identify the correspondent shape. Results show that this technique can detect the untreated area along with other features, such as leakage and holes, allowing for a high success rate of identification and for its performance at different depths, paving the way for future industry-grade quality control solutions with more complex surface analysis.

Model-based Prediction of Critical Illness in Hospitalized Patients with COVID-19.

Background The prognosis of hospitalized patients with severe coronavirus disease 2019 (COVID-19) is difficult to predict, and the capacity of intensive care units was a limiting factor during the peak of the pandemic and is generally dependent on a country's clinical resources. Purpose To determine the value of chest radiographic findings together with patient history and laboratory markers at admission to predict critical illness in hospitalized patients with COVID-19. Materials and Methods In this retrospective study, which included patients from March 7, 2020, to April 24, 2020, a consecutive cohort of hospitalized patients with real-time reverse transcription polymerase chain reaction-confirmed COVID-19 from two large Dutch community hospitals was identified. After univariable analysis, a risk model to predict critical illness (ie, death and/or intensive care unit admission with invasive ventilation) was developed, using multivariable logistic regression including clinical, chest radiographic, and laboratory findings. Distribution and severity of lung involvement were visually assessed by using an eight-point scale (chest radiography score). Internal validation was performed by using bootstrapping. Performance is presented as an area under the receiver operating characteristic curve. Decision curve analysis was performed, and a risk calculator was derived. Results The cohort included 356 hospitalized patients (mean age, 69 years ± 12 [standard deviation]; 237 men) of whom 168 (47%) developed critical illness. The final risk model's variables included sex, chronic obstructive lung disease, symptom duration, neutrophil count, C-reactive protein level, lactate dehydrogenase level, distribution of lung disease, and chest radiography score at hospital presentation. The area under the receiver operating characteristic curve of the model was 0.77 (95% CI: 0.72, 0.81; P < .001). A risk calculator was derived for individual risk assessment: Dutch COVID-19 risk model. At an example threshold of 0.70, 71 of 356 patients would be predicted to develop critical illness, of which 59 (83%) would be true-positive results. Conclusion A risk model based on chest radiographic and laboratory findings obtained at admission was predictive of critical illness in hospitalized patients with coronavirus disease 2019. This risk calculator might be useful for triage of patients to the limited number of intensive care unit beds or facilities. © RSNA, 2020 Online supplemental material is available for this article.

Development of a Long Period Fiber Grating Interrogation System Using A Multimode Laser Diode.

Optical fiber gratings have long shown their sensing capabilities. One of the main challenges, however, is the interrogation method applied, since typical systems tend to use broadband light sources with optical spectrum analyzers, laser scanning units or CCD (Charged Coupled Device) spectrometers. The following paper presents the development of an interrogation system, which explores the temperature response of a multimode laser diode, in order to interrogate long period fiber gratings. By performing a spectral sweep along one of its rejection bands, a discrete attenuation spectrum is created. Through a curve fitting technique, the original spectrum is restored. The built unit, while presenting a substantially reduced cost compared with typical interrogation systems, is capable of interrogating along a 10 nm window with measurement errors reaching minimum values as low as 0.4 nm, regarding the grating central wavelength, and 0.4 dB for its attenuation. Given its low cost and reduced dimensions, the developed system shows potential for slow-changing field applications.

Effect of Low-Doses of Gamma Radiation on Electric Arc-Induced Long Period Fiber Gratings.

This work presents an experimental study on the effects of gamma radiation on Long Period Fiber Gratings (LPFGs) in a low-dose test campaign to evaluate their eventual degradation. The study was carried out with standard single-mode fibers where the grating was inscribed using the Electric-Arc Discharge (EAD) technique. Before the gamma campaign, a detailed optical characterization was performed with repeatability tests to verify the accuracy of the setup and the associated error sources. The gamma-induced changes up to a dose of 200 krad and the recovery after radiation were monitored with the Dip Wavelength Shift (DWS). The results show that the gamma sensitivity for a total dose of 200 krad is 11 pm/krad and a total DWS of 2.3 nm has been observed with no linear dependence. Post-radiation study shows that recovery from radiation-induced wavelength shift is nearly complete in about 4000 h. Experimental results show that the changes suffered under gamma irradiation of these LPFGs are temporary making them a good choice as sensors in space applications.

Particle Classification through the Analysis of the Forward Scattered Signal in Optical Tweezers.

The ability to select, isolate, and manipulate micron-sized particles or small clusters has made optical tweezers one of the emergent tools for modern biotechnology. In conventional setups, the classification of the trapped specimen is usually achieved through the acquired image, the scattered signal, or additional information such as Raman spectroscopy. In this work, we propose a solution that uses the temporal data signal from the scattering process of the trapping laser, acquired with a quadrant photodetector. Our methodology rests on a pre-processing strategy that combines Fourier transform and principal component analysis to reduce the dimension of the data and perform relevant feature extraction. Testing a wide range of standard machine learning algorithms, it is shown that this methodology allows achieving accuracy performances around 90%, validating the concept of using the temporal dynamics of the scattering signal for the classification task. Achieved with 500 millisecond signals and leveraging on methods of low computational footprint, the results presented pave the way for the deployment of alternative and faster classification methodologies in optical trapping technologies.

Temperature Stability and Spectral Tuning of Long Period Fiber Gratings Fabricated by Femtosecond Laser Direct Writing.

Long period fiber gratings (LPFGs) were fabricated in a standard single mode fiber (SMF-28e) through femtosecond (fs) laser direct writing. LPFGs with longer and shorter periods were fabricated, which allows coupling from the fundamental core mode to lower and higher order asymmetric cladding modes (LP1,6 and LP1,12, respectively). For the grating periods of 182.7 and 192.5 µm, it was verified that the LP1,12 mode exhibits a TAP at approximately 1380 and 1448 nm in air and water, respectively. Characterization of the LPFGs subjected to high-temperature thermal treatment was accomplished. Fine-tuning of the resonance band's position and thermal stability up to 600 °C was shown. The temperature sensitivity was characterized for the gratings with different periods and for different temperature ranges. A maximum sensitivity of -180.73, and 179.29 pm/°C was obtained for the two resonances of the 182.7 µm TAP LPFG, in the range between 250 and 600 °C.

RsgA couples the maturation state of the 30S ribosomal decoding center to activation of its GTPase pocket.

During 30S ribosomal subunit biogenesis, assembly factors are believed to prevent accumulation of misfolded intermediate states of low free energy that slowly convert into mature 30S subunits, namely, kinetically trapped particles. Among the assembly factors, the circularly permuted GTPase, RsgA, plays a crucial role in the maturation of the 30S decoding center. Here, directed hydroxyl radical probing and single particle cryo-EM are employed to elucidate RsgA΄s mechanism of action. Our results show that RsgA destabilizes the 30S structure, including late binding r-proteins, providing a structural basis for avoiding kinetically trapped assembly intermediates. Moreover, RsgA exploits its distinct GTPase pocket and specific interactions with the 30S to coordinate GTPase activation with the maturation state of the 30S subunit. This coordination validates the architecture of the decoding center and facilitates the timely release of RsgA to control the progression of 30S biogenesis.

Optical fiber tips for biological applications: From light confinement, biosensing to bioparticles manipulation.

BACKGROUND: The tip of an optical fiber has been considered an attractive platform in Biology. The simple cleaved end of an optical fiber can be machined, patterned and/or functionalized, acquiring unique properties enabling the exploitation of novel optical phenomena. Prompted by the constant need to measure and manipulate nanoparticles, the invention of the Scanning Near-field Optical Microscopy (SNOM) triggered the optimization and development of novel fiber tip microfabrication methods. In fact, the fiber tip was soon considered a key element in SNOM by confining light to sufficiently small extensions, challenging the diffraction limit. As result and in consequence of the newly proposed "Lab On Tip" concept, several geometries of fiber tips were applied in three main fields: imaging (in Microscopy/Spectroscopy), biosensors and micromanipulation (Optical Fiber Tweezers, OFTs). These are able to exert forces on microparticles, trap and manipulate them for relevant applications, as biomolecules mechanical study or protein aggregates unfolding. SCOPE OF REVIEW: This review presents an overview of the main achievements, most impactful studies and limitations of fiber tip-based configurations within the above three fields, along the past 10 years. MAJOR CONCLUSIONS: OFTs could be in future a valuable tool for studying several cellular phenomena such as neurodegeneration caused by abnormal protein fibrils or manipulating organelles within cells. This could contribute to understand the mechanisms of some diseases or biophenomena, as the axonal growth in neurons. GENERAL SIGNIFICANCE: To the best of our knowledge, no other review article has so far provided such a broad view. Despite of the limitations, fiber tips have key roles in Biology/Medicine.

Plasmonic Optical Fiber Sensor Based on Double Step Growth of Gold Nano-Islands.

It is presented the fabrication and characterization of optical fiber sensors for refractive index measurement based on localized surface plasmon resonance (LSPR) with gold nano-islands obtained by single and by repeated thermal dewetting of gold thin films. Thin films of gold deposited on silica (SiO2) substrates and produced by different experimental conditions were analyzed by Scanning Electron Microscope/Dispersive X-ray Spectroscopy (SEM/EDS) and optical means, allowing identifying and characterizing the formation of nano-islands. The wavelength shift sensitivity to the surrounding refractive index of sensors produced by single and by repeated dewetting is compared. While for the single step dewetting, a wavelength shift sensitivity of ~60 nm/RIU was calculated, for the repeated dewetting, a value of ~186 nm/RIU was obtained, an increase of more than three times. It is expected that through changing the fabrication parameters and using other fiber sensor geometries, higher sensitivities may be achieved, allowing, in addition, for the possibility of tuning the plasmonic frequency.

Single Particle Differentiation through 2D Optical Fiber Trapping and Back-Scattered Signal Statistical Analysis: An Exploratory Approach.

Recent trends on microbiology point out the urge to develop optical micro-tools with multifunctionalities such as simultaneous manipulation and sensing. Considering that miniaturization has been recognized as one of the most important paradigms of emerging sensing biotechnologies, optical fiber tools, including Optical Fiber Tweezers (OFTs), are suitable candidates for developing multifunctional small sensors for Medicine and Biology. OFTs are flexible and versatile optotools based on fibers with one extremity patterned to form a micro-lens. These are able to focus laser beams and exert forces onto microparticles strong enough (piconewtons) to trap and manipulate them. In this paper, through an exploratory analysis of a 45 features set, including time and frequency-domain parameters of the back-scattered signal of particles trapped by a polymeric lens, we created a novel single feature able to differentiate synthetic particles (PMMA and Polystyrene) from living yeasts cells. This single statistical feature can be useful for the development of label-free hybrid optical fiber sensors with applications in infectious diseases detection or cells sorting. It can also contribute, by revealing the most significant information that can be extracted from the scattered signal, to the development of a simpler method for particles characterization (in terms of composition, heterogeneity degree) than existent technologies.

Fabrication of Multimode-Single Mode Polymer Fiber Tweezers for Single Cell Trapping and Identification with Improved Performance.

Optical fiber tweezers have been gaining prominence in several applications in Biology and Medicine. Due to their outstanding focusing abilities, they are able to trap and manipulate microparticles, including cells, needing any physical contact and with a low degree of invasiveness to the trapped cell. Recently, we proposed a fiber tweezer configuration based on a polymeric micro-lens on the top of a single mode fiber, obtained by a self-guided photopolymerization process. This configuration is able to both trap and identify the target through the analysis of short-term portions of the back-scattered signal. In this paper, we propose a variant of this fabrication method, capable of producing more robust fiber tips, which produce stronger trapping effects on targets by as much as two to ten fold. These novel lenses maintain the capability of distinguish the different classes of trapped particles based on the back-scattered signal. This novel fabrication method consists in the introduction of a multi mode fiber section on the tip of a single mode (SM) fiber. A detailed description of how relevant fabrication parameters such as the length of the multi mode section and the photopolymerization laser power can be tuned for different purposes (e.g., microparticles trapping only, simultaneous trapping and sensing) is also provided, based on both experimental and theoretical evidences.

Mutations in TRAPPC11 are associated with a congenital disorder of glycosylation.

Congenital disorders of glycosylation (CDG) are a heterogeneous and rapidly growing group of diseases caused by abnormal glycosylation of proteins and/or lipids. Mutations in genes involved in the homeostasis of the endoplasmic reticulum (ER), the Golgi apparatus (GA), and the vesicular trafficking from the ER to the ER-Golgi intermediate compartment (ERGIC) have been found to be associated with CDG. Here, we report a patient with defects in both N- and O-glycosylation combined with a delayed vesicular transport in the GA due to mutations in TRAPPC11, a subunit of the TRAPPIII complex. TRAPPIII is implicated in the anterograde transport from the ER to the ERGIC as well as in the vesicle export from the GA. This report expands the spectrum of genetic alterations associated with CDG, providing new insights for the diagnosis and the understanding of the physiopathological mechanisms underlying glycosylation disorders.

The association of early combined lactate and glucose levels with subsequent renal and liver dysfunction and hospital mortality in critically ill patients.

BACKGROUND: The development of renal and liver dysfunction may be accompanied by initially subtle derangements in the gluconeogenetic function. Discrepantly low glucose levels combined with high lactate levels might indicate an impaired Cori cycle. Our objective was to examine the relation between early lactate and glucose levels with subsequent renal and liver dysfunction and hospital mortality in critically ill patients. METHODS: Over a 4-year period (2011 to 2014), all adult patients admitted to our adult 48-bed teaching hospital intensive care unit (ICU) for at least 12 h were retrospectively analyzed. Lactate and glucose were regularly measured with point-of-care analyzers in all ICU patients. Lactate and glucose measurements were collected from 6 h before to 24 h after ICU admission. Patients with fewer than four lactate/glucose measurements were excluded. Patients received insulin according to a computer-guided control algorithm that aimed at a glucose level <8.0 mmol/L. Renal dysfunction was defined as the development of acute kidney injury (AKI) within 7 days, and liver function was based on the maximal bilirubin in the 7-day period following ICU admission. Mean lactate and mean glucose were classified into quintiles and univariate and multivariate analyses were related with renal and liver dysfunction and hospital mortality. Since glucose has a known U-shaped relation with outcome, we also accounted for this. RESULTS: We analyzed 92,000 blood samples from 9074 patients (63% males) with a median age of 64 years and a hospital mortality of 11%. Both lactate quintiles (≤1.0; 1.0-1.3; 1.3-1.7; 1.7-2.3; >2.3 mmol/L) and glucose quintiles (≤7.0; 7.0-7.6; 7.6-8.2; 8.2-9.0; >9.0 mmol/L) were related with outcome in univariate analysis (p < 0.001). Acute Physiology and Chronic Health Evaluation (APACHE) IV, lactate, and glucose were associated with renal and liver dysfunction in multivariate analysis (p < 0.001), with a U-shaped relationship for glucose. The combination of the highest lactate quintile with the lowest glucose quintile was associated with the highest rates of renal dysfunction, liver dysfunction, and mortality (p < 0.001) with a significant interaction between lactate and glucose (p ≤ 0.001). CONCLUSIONS: Abnormal combined lactate and glucose measurements may provide an early indication of organ dysfunction. In critically ill patients a 'normal' glucose with an elevated lactate should not be considered desirable, as this combination is related with increased mortality.

Optical fibers as beam shapers: from Gaussian beams to optical vortices.

This Letter reports a new method for the generation of optical vortices using a micropatterned optical fiber tip. Here, a spiral phase plate (2π phase shift) is micromachined on the tip of an optical fiber using a focused ion beam. This is a high resolution method that allows milling the fibers with nanoscale resolution. The plate acts as a beam tailoring system, transforming the fundamental guided mode, specifically a Gaussian mode, into the Laguerre-Gaussian mode (LG01), which carries orbital angular momentum. The experimental results are supported by computational simulations based on the finite-difference time-domain method.

From sensor fusion to knowledge distillation in collaborative LIBS and hyperspectral imaging for mineral identification.

Multimodal spectral imaging offers a unique approach to the enhancement of the analytical capabilities of standalone spectroscopy techniques by combining information gathered from distinct sources. In this manuscript, we explore such opportunities by focusing on two well-known spectral imaging techniques, namely laser-induced breakdown spectroscopy, and hyperspectral imaging, and explore the opportunities of collaborative sensing for a case study involving mineral identification. In specific, the work builds upon two distinct approaches: a traditional sensor fusion, where we strive to increase the information gathered by including information from the two modalities; and a knowledge distillation approach, where the Laser Induced Breakdown spectroscopy is used as an autonomous supervisor for hyperspectral imaging. Our results show the potential of both approaches in enhancing the performance over a single modality sensing system, highlighting, in particular, the advantages of the knowledge distillation framework in maximizing the potential benefits of using multiple techniques to build more interpretable models and paving for industrial applications.

Identification of Relevant Spectral Ranges in Laser-Induced Breakdown Spectroscopy Imaging Using the Fourier Space.

Laser-induced breakdown spectroscopy (LIBS) imaging has now a well-established position in the subject of spectral imaging, leveraging multi-element detection capabilities and fast acquisition rates to support applications both at academic and technological levels. In current applications, the standard processing pipeline to explore LIBS imaging data sets revolves around identifying an element that is suspected to exist within the sample and generating maps based on its characteristic emission lines. Such an approach requires some previous expert knowledge both on the technique and on the sample side, which hinders a wider and more transparent accessibility of the LIBS imaging technique by non-specialists. To address this issue, techniques based on visual analysis or peak finding algorithms are applied on the average or maximum spectrum, and may be employed for automatically identifying relevant spectral regions. Yet, maps containing relevant information may often be discarded due to low signal-to-noise ratios or interference with other elements. In this context, this work presents an agnostic processing pipeline based on a spatial information ratio metric that is computed in the Fourier space for each wavelength and that allows for the identification of relevant spectral ranges in LIBS. The results suggest a more robust and streamlined approach to feature extraction in LIBS imaging compared with traditional inspection of the spectra, which can introduce novel opportunities not only for spectral data analysis but also in the field of data compression.

ARDS Mortality Prediction Model Using Evolving Clinical Data and Chest Radiograph Analysis.

INTRODUCTION: Within primary ARDS, SARS-CoV-2-associated ARDS (C-ARDS) emerged in late 2019, reaching its peak during the subsequent two years. Recent efforts in ARDS research have concentrated on phenotyping this heterogeneous syndrome to enhance comprehension of its pathophysiology. METHODS AND RESULTS: A retrospective study was conducted on C-ARDS patients from April 2020 to February 2021, encompassing 110 participants with a mean age of 63.2 ± 11.92 (26-83 years). Of these, 61.2% (68) were male, and 25% (17) experienced severe ARDS, resulting in a mortality rate of 47.3% (52). Ventilation settings, arterial blood gases, and chest X-ray (CXR) were evaluated on the first day of invasive mechanical ventilation and between days two and three. CXR images were scrutinized using a convolutional neural network (CNN). A binary logistic regression model for predicting C-ARDS mortality was developed based on the most influential variables: age, PaO2/FiO2 ratio (P/F) on days one and three, CNN-extracted CXR features, and age. Initial performance assessment on test data (23 patients out of the 110) revealed an area under the receiver operating characteristic (ROC) curve of 0.862 with a 95% confidence interval (0.654-0.969). CONCLUSION: Integrating data available in all intensive care units enables the prediction of C-ARDS mortality by utilizing evolving P/F ratios and CXR. This approach can assist in tailoring treatment plans and initiating early discussions to escalate care and extracorporeal life support. Machine learning algorithms for imaging classification can uncover otherwise inaccessible patterns, potentially evolving into another form of ARDS phenotyping. The combined features of these algorithms and clinical variables demonstrate superior performance compared to either element alone.

A Novel Ligamentous Complex in the Anteromedial Region of the Knee: A Cadaveric Study.

Background: The medial knee structures have a primary role in stabilizing valgus and rotational stress, which makes them important in assessing the ligament-injured knee globally and choosing the most adequate treatment. Purpose: To conduct a layer-by-layer dissection of the knee's anteromedial side and provide a qualitative and quantitative description of the anatomy and histology of a ligament in the anteromedial region of the knee, which we have termed the anterior oblique ligament (AOL). Also, to describe the AOL relationship with what we have termed the medial cross-a ligament complex that stabilizes the medial pivot. Study Design: Descriptive laboratory study. Methods: A total of 35 fresh-frozen knees from transfemoral amputations that were exclusively performed for vascular reasons were dissected. Structures were identified after meticulous dissection, respecting the same protocol, measured with a digital caliper rule, and histologically studied for data. Results: The AOL was found in all dissected knees, with a mean length of 31.47 ± 5.06 mm. This structure presented a ligament histology with densely organized collagen fibrils. The medial cross was represented by the superficial medial collateral ligament, AOL (anterior region), and posterior oblique ligament. Conclusion: This study demonstrated the presence of a ligament in the anteromedial region of the knee, termed the AOL. This structure was in the anterior part of a ligament complex-the medial cross. Clinical Relevance: Studying and revisiting the medial compartment can provide important information for understanding joint instability and promoting better results in ligament reconstructions.

Anterior Cruciate and Anterior Oblique Ligament Reconstruction Using Hamstrings and Peroneus Longus' Anterior Half Grafts.

Anterior cruciate ligament injuries are common in high school and college with an estimated 120,000 cases per year in the United States. Most sports injuries occur without direct contact, and knee valgus with external rotation of the foot is the most common movement. This movement may be related to the injury of the anterior oblique ligament located in the anteromedial quadrant of the knee. This technical note presents anterior cruciate ligament reconstruction with extraarticular anteromedial reinforcement using hamstring and the anterior half of the peroneus longus grafts.