Counterdiabatic driving for long-lived singlet state preparation.

The quantum adiabatic method, which maintains populations in their instantaneous eigenstates throughout the state evolution, is an established and often a preferred choice for state preparation and manipulation. Although it minimizes the driving cost significantly, its slow speed is a severe limitation in noisy intermediate-scale quantum era technologies. Since adiabatic paths are extensive in many physical processes, it is of broader interest to achieve adiabaticity at a much faster rate. Shortcuts to adiabaticity techniques, which overcome the slow adiabatic process by driving the system faster through non-adiabatic paths, have seen increased attention recently. The extraordinarily long lifetime of the long-lived singlet states (LLS) in nuclear magnetic resonance (NMR), established over the past decade, has opened several important applications ranging from spectroscopy to biomedical imaging. Various methods, including adiabatic methods, are already being used to prepare LLS. In this article, we report the use of counterdiabatic driving (CD) to speed up LLS preparation with faster drives. Using NMR experiments, we show that CD can give stronger LLS order in shorter durations than conventional adiabatic driving.

Return to play after shoulder instability in National Football League athletes.

HYPOTHESIS: We hypothesized that National Football League (NFL) players sustaining a shoulder destabilizing injury could return to play (RTP) successfully at a high rate regardless of treatment type. METHODS: We identified and evaluated 83 NFL players who sustained an in-season shoulder instability event while playing in the NFL. NFL RTP, incidence of surgery, time to RTP, recurrent instability events, seasons/games played after the injury, and demographic data were collected. Overall RTP was determined, and players who did and did not undergo operative repair were compared. RESULTS: Ninety-two percent of NFL players returned to NFL regular season play at a median of 0.0 weeks in those sustaining a shoulder subluxation and 3.0 weeks in those sustaining a dislocation who did not undergo surgical repair (P = .029). Players who underwent operative repair returned to play at a median of 39.3 weeks. Forty-seven percent of players had a recurrent instability event. For players who were able to RTP, those who underwent surgical repair (31%) had a lower recurrence rate (26% vs. 55%, P = .021) and longer interval between a recurrent instability event after RTP (14.7 vs. 2.5 weeks, P = .050). CONCLUSION: There is a high rate of RTP after shoulder instability events in NFL players. Players who sustain shoulder subluxations RTP faster but are more likely to experience recurrent instability than those with shoulder dislocations. Surgical stabilization of the shoulder after an instability event decreases the chances of a second instability event and affords a player a greater interval between the initial injury and a recurrent event.

Laparoscopic laser lithotripsy inside the endocatch bag: An alternative technique for removal of large post lap pyelolithotomy calculi.

Large staghorn calculi in unascended pelvic kidneys and in normally located kidneys with anatomy unsuitable for percutaneous nephrolithotomy have to be treated via pyelolithotomy. When performed laparoscopically, the extraction of these staghorn calculi, without extending skin incision at the port site is challenging. We describe the successful use of laparoscopic laser lithotripsy, intracorporeally, with the entrapped calculus inside the endocatch bag, for fragmentation and retrieval without extension of skin incision.

Accounting for tissue heterogeneity in infrared spectroscopic imaging for accurate diagnosis of thyroid carcinoma subtypes.

Fourier transform infrared (FT-IR) microscopy was used to image tissue samples from twenty patients diagnosed with thyroid carcinoma. The spectral data were then used to differentiate between follicular thyroid carcinoma and follicular variant of papillary thyroid carcinoma using principle component analysis coupled with linear discriminant analysis and a Naïve Bayesian classifier operating on a set of computed spectral metrics. Classification of patients' disease type was accomplished by using average spectra from a wide region containing follicular cells, colloid, and fibrosis; however, classification of disease state at the pixel level was only possible when the extracted spectra were limited to follicular epithelial cells in the samples, excluding the relatively uninformative areas of fibrosis. The results demonstrate the potential of FT-IR microscopy as a tool to assist in the difficult diagnosis of these subtypes of thyroid cancer, and also highlights the importance of selectively and separately analyzing spectral information from different features of a tissue of interest.

A label-free approach by infrared spectroscopic imaging for interrogating the biochemistry of diabetic nephropathy progression.

Routine histology, the current gold standard, involves staining for specific biomolecules. However, untapped biochemical information in tissue can be gathered using biochemical imaging. Infrared spectroscopy is an emerging modality that allows label-free chemical imaging to derive biochemical information (such as protein, lipids, DNA, collagen) from tissues. Here we employed this technology in order to better predict the development of diabetic nephropathy. Using human primary kidney biopsies or nephrectomies, we obtained tissue from 4 histologically normal kidneys, 4 histologically normal kidneys from diabetic subjects, and 5 kidneys with evidence of diabetic nephropathy. A biochemical signature of diabetic nephropathy was derived that enabled prediction of nephropathy based on the ratio of only 2 spectral frequencies. Nonetheless, using the entire spectrum of biochemical information, we were able to detect renal disease with near-perfect accuracy. Additionally, study of sequential protocol biopsies from 3 transplanted kidneys showed biochemical changes even prior to clinical manifestation of diabetic nephropathy. Thus, infrared imaging can identify critical biochemical alterations that precede morphologic changes, potentially allowing for earlier intervention.

MCMC Methods for Parameter Estimation in ODE Systems for CAR-T Cell Cancer Therapy.

Chimeric antigen receptor (CAR)-T cell therapy represents a breakthrough in treating resistant hematologic cancers. It is based on genetically modifying T cells transferred from the patient or a donor. Although its implementation has increased over the last few years, CAR-T has many challenges to be addressed, for instance, the associated severe toxicities, such as cytokine release syndrome. To model CAR-T cell dynamics, focusing on their proliferation and cytotoxic activity, we developed a mathematical framework using ordinary differential equations (ODEs) with Bayesian parameter estimation. Bayesian statistics were used to estimate model parameters through Monte Carlo integration, Bayesian inference, and Markov chain Monte Carlo (MCMC) methods. This paper explores MCMC methods, including the Metropolis-Hastings algorithm and DEMetropolis and DEMetropolisZ algorithms, which integrate differential evolution to enhance convergence rates. The theoretical findings and algorithms were validated using Python and Jupyter Notebooks. A real medical dataset of CAR-T cell therapy was analyzed, employing optimization algorithms to fit the mathematical model to the data, with the PyMC library facilitating Bayesian analysis. The results demonstrated that our model accurately captured the key dynamics of CAR-T cell therapy. This conclusion underscores the potential of parameter estimation to improve the understanding and effectiveness of CAR-T cell therapy in clinical settings.

Thymic masses and mimics in adults: review of common and uncommon pathologies.

The thymus is a primary lymphoid organ that plays a key role in the immune system development. Normally, it is located in the anterior mediastinum and it changes tissue composition with progressive fatty involution with age. The spectrum of pathological processes involving the thymus include enlargement, tumour development, and cystic change. In addition, other local pathology can mimic thymic disease. Differentiating these entities can be challenging; however, recognizing key features on imaging is essential to appropriately guide further investigation and therapy. The focus of this pictorial review will be to highlight the important distinguishing features of thymic hyperplasia, thymomas, thymic cysts, thymic neuroendocrine tumours (NETs), thymolipomas, mediastinal teratomas, and other mimics of thymic disease. Knowledge of the varying imaging findings on computed tomography and magnetic resonance imaging is valuable for radiologists to appropriately classify disease, avoid misdiagnosis, and expedite therapy.

Pyogenic hepatic abscesses secondary to choledocholithiasis eight years post-cholecystectomy: A case report.

Cholecystectomy is the gold standard surgical treatment for acute calculous cholecystitis. Only approximately 0.4 % of these patients subsequently develop choledocholithiasis. The incidence of hepatic abscesses in these patients is unknown, but is likely low, considering there are approximately 2-15 cases of hepatic abscesses per 100,000 people in the US. The authors report the case of a 62-year-old man whose CT scan revealed hepatic abscesses secondary to choledocholithiasis, eight years after a cholecystectomy.

On the systematic status of Calliophis macclellandi nigriventer Wall, 1908 (Reptilia: Serpentes: Elapidae).

Sinomicrurus macclellandi (Reinhardt, 1844) is a species of coral snakes distributed across the forests of Southeast Asia and the Himalayas. The species exhibits distinct forms across its range, and it has been classified into four subspecies. Calliophis macclellandi nigriventer Wall, 1908 a population from Western Himalayas, which was described as a variety, has not been attended to until now. Our study of a recently collected specimen from near Solan, Himachal Pradesh, India and existing museum material has allowed us to assess the validity of this population based on molecular and morphological data and has given us enough evidence to suggest its elevation to a species rank. Sinomicrurus nigriventer comb. nov. was found to be embedded within a clade comprising S. peinani, but not S. macclellandi s. l., with a genetic distance of 7-16% from its congeners. Morphologically, it differs from its congeners in having a reddish brown dorsum and a mid-dorsal black vertebral strip extending from the nape to the vent and with three thin bands on the tail, belly white with black smear up to the vent, tail dorsum with a few band-like blotches, and males with 230-235 ventral scales.

Hyperspectral Tissue Image Segmentation Using Semi-Supervised NMF and Hierarchical Clustering.

Hyperspectral imaging (HSI) of tissue samples in the mid-infrared (mid-IR) range provides spectro-chemical and tissue structure information at sub-cellular spatial resolution. Disease states can be directly assessed by analyzing the mid-IR spectra of different cell types (e.g., epithelial cells) and sub-cellular components (e.g., nuclei), provided that we can accurately classify the pixels belonging to these components. The challenge is to extract information from hundreds of noisy mid-IR bands at each pixel, where each band is not very informative in itself, making annotations of unstained tissue HSI images particularly tricky. Because the tissue structure is not necessarily identical between the two sections, only a few regions in unstained HSI image can be annotated with high confidence, even when serial (or adjacent) hematoxylin and eosin stained section is used as a visual guide. In order to completely use both labeled and unlabeled pixels in training images, we have developed an HSI pixel classification method that uses semi-supervised learning for both spectral dimension reduction and hierarchical pixel clustering. Compared to the supervised classifiers, the proposed method was able to account for the vast differences in the spectra of sub-cellular components of the same cell type and to achieve an F1 score of 71.18% on twofold cross-validation across 20 tissue images. To generate further interest in this promising modality, we have released our source code and also showed that disease classification is straightforward after HSI image segmentation.

Label-free Identification of Antibody-mediated Rejection in Cardiac Allograft Biopsies Using Infrared Spectroscopic Imaging.

BACKGROUND: Antibody-mediated rejection (AMR) in cardiac allograft recipients remains less well-understood than acute cellular rejection, is associated with worse outcomes, and portends a greater risk of developing chronic allograft vasculopathy. Diffuse immunohistochemical C4d staining of capillary endothelia in formalin-fixed, paraffin-embedded right ventricular endomyocardial biopsies is diagnostic of immunopathologic AMR but serves more as a late-stage marker. Infrared (IR) spectroscopy may be a useful tool in earlier detection of rejection. We performed mid-IR spectroscopy to identify a unique biochemical signature for AMR. METHODS: A total of 30 posttransplant formalin-fixed paraffin-embedded right ventricular tissue biopsies (14 positive for C4d and 16 negative for C4d) and 14 native heart biopsies were sectioned for IR analysis. Infrared images of entire sections were acquired and regions of interest from cardiomyocytes were identified. Extracted spectra were averaged across many pixels within each region of interest. Principal component analysis coupled with linear discriminant analysis and predictive classifiers were applied to the data. RESULTS: Comparison of averaged mid-IR spectra revealed unique features among C4d-positive, C4d-negative, and native heart biopsies. Principal component analysis coupled with linear discriminant analysis and classification models demonstrated that spectral features from the mid-IR fingerprint region of these 3 groups permitted accurate automated classification into each group. CONCLUSIONS: In cardiac allograft biopsies with immunopathologic AMR, IR spectroscopy reveals a biochemical signature unique to AMR compared with that of nonrejecting cardiac allografts and native hearts. Future study will focus on the predictive capabilities of this IR signature.

Predicting Fibrosis Progression in Renal Transplant Recipients Using Laser-Based Infrared Spectroscopic Imaging.

Renal transplants have not seen a significant improvement in their 10-year graft life. Chronic damage accumulation often leads to interstitial fibrosis and tubular atrophy (IF/TA) and thus graft function loss over time. For this reason, IF/TA has been the chief suspect for a potential prognostic marker for long term outcomes. In this study, we have used infrared spectroscopic (IR) imaging to interrogate the biochemistry of regions of fibrosis from renal transplant biopsies to identify a biochemical signature that can predict rapid progression of fibrosis. IR imaging represents an approach that permits label-free biochemical imaging of human tissues towards identifying novel biomarkers for disease diagnosis or prognosis. Two cohorts were identified as progressors (n = 5, > 50% fibrosis increase between time points) and non-progressors (n = 5, < 5% increase between time points). Each patient had an early time point and late time point biopsy. Collagen associated carbohydrate moieties (ν(C-O), 1035 cm-1 and ν(C-O-C),1079 cm-1) spectral ratios demonstrated good separation between the two cohorts (p = 0.001). This was true for late and early time point biopsies suggesting the regions of fibrosis are biochemically altered in cases undergoing progressive fibrosis. Thus, IR imaging can potentially predict rapid progression of fibrosis using histologically normal early time point biopsies.

Infrared spectroscopic imaging: Label-free biochemical analysis of stroma and tissue fibrosis.

Infrared spectroscopic tissue imaging is a potentially powerful adjunct tool to current histopathology techniques. By coupling the biochemical signature obtained through infrared spectroscopy to the spatial information offered by microscopy, this technique can selectively analyze the chemical composition of different features of unlabeled, unstained tissue sections. In the past, the tissue features that have received the most interest were parenchymal and epithelial cells, chiefly due to their involvement in dysplasia and progression to carcinoma; however, the field has recently turned its focus toward stroma and areas of fibrotic change. These components of tissue present an untapped source of biochemical information that can shed light on many diverse disease processes, and potentially hold useful predictive markers for these same pathologies. Here we review the recent applications of infrared spectroscopic imaging to stromal and fibrotic regions of diseased tissue, and explore the potential of this technique to advance current capabilities for tissue analysis.

Infrared spectroscopic imaging detects chemical modifications in liver fibrosis due to diabetes and disease.

The importance of stroma as a rich diagnostic region in tissue biopsies is growing as there is an increasing understanding that disease processes in multiple organs can affect the composition of adjacent connective tissue regions. This may be especially true in the liver, since this organ's central metabolic role exposes it to multiple disease processes. We use quantum cascade laser infrared spectroscopic imaging to study changes in the chemical status of hepatocytes and fibrotic regions of liver tissue that result from the progression of liver cirrhosis to hepatocellular carcinoma and the potentially confounding effects of diabetes mellitus.

High-definition Fourier Transform Infrared (FT-IR) spectroscopic imaging of human tissue sections towards improving pathology.

High-definition Fourier Transform Infrared (FT-IR) spectroscopic imaging is an emerging approach to obtain detailed images that have associated biochemical information. FT-IR imaging of tissue is based on the principle that different regions of the mid-infrared are absorbed by different chemical bonds (e.g., C=O, C-H, N-H) within cells or tissue that can then be related to the presence and composition of biomolecules (e.g., lipids, DNA, glycogen, protein, collagen). In an FT-IR image, every pixel within the image comprises an entire Infrared (IR) spectrum that can give information on the biochemical status of the cells that can then be exploited for cell-type or disease-type classification. In this paper, we show: how to obtain IR images from human tissues using an FT-IR system, how to modify existing instrumentation to allow for high-definition imaging capabilities, and how to visualize FT-IR images. We then present some applications of FT-IR for pathology using the liver and kidney as examples. FT-IR imaging holds exciting applications in providing a novel route to obtain biochemical information from cells and tissue in an entirely label-free non-perturbing route towards giving new insight into biomolecular changes as part of disease processes. Additionally, this biochemical information can potentially allow for objective and automated analysis of certain aspects of disease diagnosis.