"Quality of life is impaired in children with chronic pancreatitis: A multicenter study".

BACKGROUND AND OBJECTIVES: The impact of chronic pancreatitis (CP) on quality of life (QOL) of children is not well established. Our objective was to evaluate the QOL, identify contributing factors, and determine the prevalence of anxiety and depression in children with CP in India. METHODS: Children (8-18y old) with CP were prospectively enrolled across three pediatric gastroenterology centres in India. QOL was assessed using the pediatric QOL inventory (PedsQL 4.0) scale, administered to both children and their parents. Anxiety and depression was studied using the Revised Children's Anxiety and Depression Scale (RCADS 25). Contributing factors were identified using binary logistic regression analysis. The data was compared against published QOL data in healthy Indian children. RESULTS: 121 children with CP (boys-57.9 %, age at QOL-14 ± 3.2years) were enrolled. A majority (82.7 %) had pain and advanced disease (Cambridge grade IV- 63.6 %). Children with CP had poorer QOL compared to controls (total score 74.6 ± 16 vs. 87.5 ± 11.1, p < 0.0001). QOL scores were similar across centres. Older children were similar to younger ones, except for a poorer emotional QOL. Taking QOL < -2 standard deviation (SD) of controls, ∼35 % had poor physical (50.9 ± 11.9) and 20 % had poor psychosocial (PS) QOL score (52.1 ± 7.2). On analysis, presence of pain and lower socio-economic status (SES) adversely affected both physical and PS-QOL. Additionally, girls had poorer PS-QOL than boys (Odds ratio 3.1, 95%CI:1.23-7.31). Anxiety and depression were uncommon (2,1.6 %). CONCLUSIONS: Patients with CP had impaired physical and psycho-social QOL. Presence of pain and lower SES adversely affected QOL. Psychiatric comorbidities were uncommon.

Machine Learning-Enabled Image Classification for Automated Electron Microscopy.

Traditionally, materials discovery has been driven more by evidence and intuition than by systematic design. However, the advent of "big data" and an exponential increase in computational power have reshaped the landscape. Today, we use simulations, artificial intelligence (AI), and machine learning (ML) to predict materials characteristics, which dramatically accelerates the discovery of novel materials. For instance, combinatorial megalibraries, where millions of distinct nanoparticles are created on a single chip, have spurred the need for automated characterization tools. This paper presents an ML model specifically developed to perform real-time binary classification of grayscale high-angle annular dark-field images of nanoparticles sourced from these megalibraries. Given the high costs associated with downstream processing errors, a primary requirement for our model was to minimize false positives while maintaining efficacy on unseen images. We elaborate on the computational challenges and our solutions, including managing memory constraints, optimizing training time, and utilizing Neural Architecture Search tools. The final model outperformed our expectations, achieving over 95% precision and a weighted F-score of more than 90% on our test data set. This paper discusses the development, challenges, and successful outcomes of this significant advancement in the application of AI and ML to materials discovery.

Incidence, Predictors, and Outcomes of Venous and Arterial Thrombosis in COVID-19: A Nationwide Inpatient Analysis.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is known to increase the risk of venous thromboembolism (VTE) and arterial thromboembolism (ATE). However, the incidence, predictors, and outcomes of clinical thrombosis for inpatients with COVID-19 are not well known. This study aimed to enhance our understanding of clinical thrombosis in COVID-19, its associated factors, and mortality outcomes. METHOD: Hospitalised adult (≥18 years of age) patients with COVID-19 in 2020 were retrospectively identified from the US National Inpatient Sample database. Clinical characteristics, incident VTE, ATE, and in-hospital mortality outcomes were recorded. Multivariable logistic regression was performed to identify clinical factors associated with thrombosis and in-hospital mortality in COVID-19 inpatients. RESULTS: A total of 1,583,135 adult patients with COVID-19 in the year 2020 were identified from the National Inpatient Sample database; patients with thrombosis were 41% females with a mean age of 65.4 (65.1-65.6) years. The incidence of thrombosis was 6.1% (97,185), including VTE at 4.8% (76,125), ATE at 3.0% (47,790), and the in-hospital mortality rate was 13.4% (212,785). Patients with thrombosis were more likely to have respiratory symptoms of COVID-19 (76.7% vs 75%, p<0.001) compared with patients without thrombosis. The main factors associated with overall thrombosis, VTE, and ATE were paralysis, ventilation, solid tumours without metastasis, metastatic cancer, and acute liver failure. Although all thrombosis categories were associated with higher in-hospital mortality for COVID-19 inpatients in univariable analyses (p<0.001), they were not in multivariable analyses-thrombosis (odds ratio [OR] 1.24; 95% confidence interval [CI] 0.90-1.70; p=0.19), VTE (OR 0.70; 95% CI 0.52-1.00; p=0.05), and ATE (OR 1.07; 95% CI 0.92-1.25; p=0.36). CONCLUSIONS: The association of COVID-19 with thrombosis and VTE increases with increasing severity of the COVID-19 disease. Risk stratification of thrombosis is crucial in COVID-19 patients to determine the necessity of thromboprophylaxis.

MPpredictor: An Artificial Intelligence-Driven Web Tool for Composition-Based Material Property Prediction.

The applications of artificial intelligence, machine learning, and deep learning techniques in the field of materials science are becoming increasingly common due to their promising abilities to extract and utilize data-driven information from available data and accelerate materials discovery and design for future applications. In an attempt to assist with this process, we deploy predictive models for multiple material properties, given the composition of the material. The deep learning models described here are built using a cross-property deep transfer learning technique, which leverages source models trained on large data sets to build target models on small data sets with different properties. We deploy these models in an online software tool that takes a number of material compositions as input, performs preprocessing to generate composition-based attributes for each material, and feeds them into the predictive models to obtain up to 41 different material property values. The material property predictor is available online at http://ai.eecs.northwestern.edu/MPpredictor.

Post-cardiac injury syndrome after surgical repair of atrial septal defect: Reporting a rare occurrence.

A 16-year-old male with past medical history of congenital atrial septal defect surgical repair, presented with recurrent pericarditis secondary to post-cardiotomy injury syndrome (PCIS), After failing medical therapy, he ultimately underwent pericardiectomy for symptom resolution, PCIS is underdiagnosed in children and should be considered in patients with recurrent chest, pain.

Renal Outcomes Following Transcatheter Mitral Valve Repair - Analysis of COAPT Trial Data.

The prevalence of valvular heart disease in the United States has been estimated at 4.2-to-5.6 million, with mitral regurgitation (MR) being the most common lesion. Significant MR is associated with heart failure (HF) and death if left untreated. When HF is present, renal dysfunction (RD) is common and is associated with worse outcomes (ie, it is a marker of HF disease progression). Additionally, a complex interplay exists in patients with HF who also have MR, as this combination further impairs renal function, and the presence of RD further worsens prognosis and often limits guideline-directed management and therapy (GDMT). This has important implications in secondary MR because GDMT is the standard of care. However, with the development of minimally invasive transcatheter mitral valve repair, mitral transcatheter edge-to-edge repair (TEER) has become a new treatment option for secondary MR that is now incorporated into current guidelines published in 2020 that listed mitral TEER as a class 2a recommendation (moderate recommendation with benefit >> risk) as an addition to GDMT in a subset of patients with left ventricular ejection fraction <50%. The Cardiovascular Outcomes Assessment of the MitraClip Percutaneous Therapy for Heart Failure Patients with Functional Mitral Regurgitation (COAPT) trial, which demonstrated favorable outcomes in secondary MR by adding mitral TEER to GDMT versus GDMT alone, was the evidence base for these guidelines. Considering these guidelines and the understanding that concomitant RD often limits GDMT in secondary MR, there is emerging research studying the renal outcomes from the COAPT trial. This review analyzes this evidence, which could further influence current decision-making and future guidelines.

One-year clinical and echocardiographic outcomes of transcatheter aortic valve replacement with SAPIEN 3 Ultra versus SAPIEN 3.

BACKGROUND: The newest-generation balloon-expandable valve, SAPIEN 3 Ultra (S3U), is expected to function well with the enhanced sealing skirt compared with SAPIEN 3 (S3). However, current literature on the comparison between these two valves is limited to short-term follow-ups. Therefore, we aimed to evaluate the 1-year outcomes and echocardiographic changes of S3U compared with S3. METHODS: We retrospectively identified patients who underwent transfemoral-transcatheter aortic valve replacement with S3U or S3 (20/23/26 mm) at our institution in 2018-2020. Outcomes were 1-year clinical events and echocardiographic parameters, and were compared between S3U and S3 after adjustment with inverse probability of treatment weighting. RESULTS: The S3U and S3 groups included 297 (25.7%) and 858 (74.3%) patients, respectively. There were no significant differences between the two groups in clinical events (death 5.8% vs. 5.5%, hazard ratio [HR] 1.07, 95% confidence interval [CI] 0.81-1.90; death or heart failure hospitalization 10.3% vs. 10.1%, HR 1.04, 95% CI 0.67-1.62). The S3U group had a lower prevalence of mild paravalvular leakage (PVL) (13.7% vs. 22.3%, p = 0.044), with similar moderate PVL (0.7% vs. 1.2%, p > 0.99). No significant differences were observed in aortic valve mean gradient and Doppler velocity index at 1 year. However, the S3U group had a larger increase in mean gradient from implantation to 1 year (median +4.70 vs. +1.63 mmHg, p < 0.001). CONCLUSIONS: S3U and S3 carried similarly favorable clinical event risks. Nonetheless, S3U was associated with less frequent mild PVL but a larger increase in transprosthetic gradient. Further studies are needed to determine the prognostic impact of these hemodynamic differences.

Radiation reduction in a modern catheterization laboratory: A single-center experience.

BACKGROUND: Measures were undertaken at the Cleveland Clinic to reduce radiation exposure to patients and personnel working in the catheterization laboratories. We report our experience with these improved systems over a 7-year period in patients undergoing diagnostic catheterization (DC) and percutaneous coronary interventions (PCIs). METHODS: Patients were categorized into preinitiative (2009-2012) and postinitiative (2013-2019) groups in the DC and PCI cohorts. Propensity score matching was done between the pre- and postinitiative groups for both cohorts based on age, sex, body surface area, total fluoroscopy time, and total acquisition time. The effectiveness of radiation reduction measures was assessed by comparing the total air kerma (Ka,r ), and fluoroscopy- and acquisition-mode air kerma in patients in the two groups. RESULTS: In the DC cohort, there was a significant reduction in Ka,r in the postinitiative group in comparison to the preinitiative group (median, 396 vs. 857 mGy; p < 0.001). In the PCI cohort, Ka,r in the postinitiative group was 1265 mGy, which was significantly lower than the corresponding values in the preinitiative group (1994 mGy; p < 0.001). We also observed a significant reduction in fluoroscopy- and acquisition-based air kerma rates, and air kerma area product in the postinitiative group in comparison to the preinitiative group in both matched and unmatched DC and PCI cohorts after the institution of radiation reduction measures. CONCLUSION: There was a significant and sustained reduction in radiation exposure to patients in the catheterization laboratory with the implementation of advanced protocols. Similar algorithms can be applied in other laboratories to achieve a similar reduction in radiation exposure.

Cerebral embolic protection and severity of stroke following transcatheter aortic valve replacement.

BACKGROUND: The cerebral embolic protection (CEP) device captures embolic debris during transcatheter aortic valve replacement (TAVR). However, the impact of CEP on stroke severity following TAVR remains unclear. Therefore, we aimed to examine whether CEP was associated with reduced severity of stroke following TAVR. METHODS: This was a retrospective cohort study of 2839 consecutive patients (mean age: 79.2 ± 9.5 years, females: 41.5%) who underwent transfemoral TAVR at our institution between 2013 and 2020. We categorized patients into Sentinel CEP users and nonusers. Neuroimaging data were reviewed and the final diagnosis of a cerebrovascular event was adjudicated by a neurologist blinded to the CEP use or nonuse. We compared the incidence and severity (assessed by the National Institutes of Health Stroke Scale [NIHSS]) of stroke through 72 h post-TAVR or discharge between the two groups using stabilized inverse probability of treatment weighting (IPTW) of propensity scores. RESULTS: Of the eligible patients, 1802 (63.5%) received CEP during TAVR and 1037 (36.5%) did not. After adjustment for patient characteristics by stabilized IPTW, the rate of overall stroke was numerically lower in CEP users than in CEP nonusers, but the difference did not reach statistical significance (0.49% vs. 1.18%, p = 0.064). However, CEP users had significantly lower rates of moderate-or-severe stroke (NIHSS ≥ 6: 0.11% vs. 0.69%, p = 0.013) and severe stroke (NIHSS ≥ 15: 0% vs. 0.29%, p = 0.046). Stroke following CEP use (n = 8), compared with stroke following CEP nonuse (n = 15), tended to carry a lower NIHSS (median [IQR], 4.0 [2.0-7.0] vs. 7.0 [4.5-19.0], p = 0.087). Four (26.7%) out of 15 patients with stroke following CEP nonuse died within 30 days, with no death after stroke following CEP use. CONCLUSIONS: CEP use may be associated with attenuated severity of stroke despite no significant difference in overall stroke incidence compared with CEP nonuse. This finding is considered hypothesis-generating and needs to be confirmed in large prospective studies.

Nanoparticle-eluting stents for coronary intervention: formulation, characterization, and in vitro evaluation.

Coronary artery disease (CAD) is currently a leading cause of death worldwide. In the history of percutaneous coronary intervention for the treatment of CAD, a drug-eluting stent (DES) is recognized as a revolutionary technology that has the unique ability to significantly reduce restenosis and provide both mechanical and biological solutions simultaneously to the target lesion. The aim of the research work was to design and fabricate DES coated with a nanoparticulate drug formulation. Sirolimus, an inhibitor of the smooth muscle cell (SMC) proliferation and migration, was encapsulated in polymeric nanoparticles (NPs). The NP formulation was characterized for various physicochemical parameters. Cell viability and cell uptake studies were performed using human coronary artery smooth muscle cells (HCASMCs). The developed NP formulation showed enhanced efficacy compared to plain drug solution and exhibited time-dependent uptake into the HCASMCs. The developed NP formulation was coated on the Flexinnium™ ultra-thin cobalt-chromium alloy coronary stent platform. The NP-coated stents were characterized for morphology and residual solvent analysis. In vitro drug release was also evaluated. Ex vivo arterial permeation was carried out to evaluate the NP uptake from the surface of the stents. The characterization studies together corroborated that the developed NP coated stent can be a promising replacement of the current DESs.

Generation of pre-tRNAs from polycistronic operons is the essential function of RNase P in Escherichia coli.

Ribonuclease P (RNase P) is essential for the 5'-end maturation of tRNAs in all kingdoms of life. In Escherichia coli, temperature sensitive mutations in either its protein (rnpA49) and or RNA (rnpB709) subunits lead to inviability at nonpermissive temperatures. Using the rnpA49 temperature sensitive allele, which encodes a partially defective RNase P at the permissive temperature, we show here for the first time that the processing of RNase P-dependent polycistronic tRNA operons to release pre-tRNAs is the essential function of the enzyme, since the majority of 5'-immature tRNAs can be aminoacylated unless their 5'-extensions ≥8 nt. Surprisingly, the failure of 5'-end maturation elicits increased polyadenylation of some pre-tRNAs by poly(A) polymerase I (PAP I), which exacerbates inviability. The absence of PAP I led to improved aminoacylation of 5'-immature tRNAs. Our data suggest a more dynamic role for PAP I in maintaining functional tRNA levels in the cell.

Mortality in Adult Congenital Heart Disease: Analysis of Outcomes and Risk Stratification.

Adult congenital heart disease (ACHD) is a rising concern for the current healthcare system, with a prevalence that is anticipated to steadily increase through the year 2050. It is estimated that there are >1.4 million adults in the United States living with a congenital heart defect. Despite significant advances in medical and surgical therapy, most of these patients progress to advanced heart failure due to the unique anatomic, physiological, and hemodynamic abnormalities associated with the disease. Patient awareness of the disease coupled with advances in the diagnosis and treatment has led to a significant increase in the surgical treatment of CHD in adults. The authors aim to summarize and critically appraise the current literature on the morbidity, mortality, and risk scores associated with ACHD.

Gelation of plasmonic metal oxide nanocrystals by polymer-induced depletion attractions.

Gelation of colloidal nanocrystals emerged as a strategy to preserve inherent nanoscale properties in multiscale architectures. However, available gelation methods to directly form self-supported nanocrystal networks struggle to reliably control nanoscale optical phenomena such as photoluminescence and localized surface plasmon resonance (LSPR) across nanocrystal systems due to processing variabilities. Here, we report on an alternative gelation method based on physical internanocrystal interactions: short-range depletion attractions balanced by long-range electrostatic repulsions. The latter are established by removing the native organic ligands that passivate tin-doped indium oxide (ITO) nanocrystals while the former are introduced by mixing with small PEG chains. As we incorporate increasing concentrations of PEG, we observe a reentrant phase behavior featuring two favorable gelation windows; the first arises from bridging effects while the second is attributed to depletion attractions according to phase behavior predicted by our unified theoretical model. Our assembled nanocrystals remain discrete within the gel network, based on X-ray scattering and high-resolution transmission electron microscopy. The infrared optical response of the gels is reflective of both the nanocrystal building blocks and the network architecture, being characteristic of ITO nanocrystals' LSPR with coupling interactions between neighboring nanocrystals.

Dual-Mode Infrared Absorption by Segregating Dopants within Plasmonic Semiconductor Nanocrystals.

When aliovalent dopants are sufficiently segregated to the core or near the surface of semiconductor nanocrystals, charge carriers donated by the dopants are also segregated to the core or near the surface, respectively. In Sn-doped indium oxide nanocrystals, we find that this contrast in free charge carrier concentration creates a core and shell with differing dielectric properties and results in two distinctly observable plasmonic extinction peaks. The trends in this dual-mode optical response with shell growth differ from core/shell nanoparticles composed of traditional plasmonic metals such as Au and Ag. We developed a model employing a core/shell effective medium approximation that can fit the dual-mode spectra and explain the trends in the extinction response. Lastly, we show that dopant segregation can improve sensitivity of plasmon spectra to changes in refractive index of the surrounding environment.

Nonequilibrium Biophysical Processes Influence the Large-Scale Architecture of the Cell Nucleus.

Model approaches to nuclear architecture have traditionally ignored the biophysical consequences of ATP-fueled active processes acting on chromatin. However, transcription-coupled activity is a source of stochastic forces that are substantially larger than the Brownian forces present at physiological temperatures. Here, we describe an approach to large-scale nuclear architecture in metazoans that incorporates cell-type-specific active processes. The model predicts the statistics of positional distributions, shapes, and overlaps of each chromosome. Simulations of the model reproduce common organizing principles underlying large-scale nuclear architecture across human cell nuclei in interphase. These include the differential positioning of euchromatin and heterochromatin, the territorial organization of chromosomes (including both gene-density-based and size-based chromosome radial positioning schemes), the nonrandom locations of chromosome territories, and the shape statistics of individual chromosomes. We propose that the biophysical consequences of the distribution of transcriptional activity across chromosomes should be central to any chromosome positioning code.

Author Correction: Impacts of surface depletion on the plasmonic properties of doped semiconductor nanocrystals.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Localized Surface Plasmon Resonance in Semiconductor Nanocrystals.

Localized surface plasmon resonance (LSPR) in semiconductor nanocrystals (NCs) that results in resonant absorption, scattering, and near field enhancement around the NC can be tuned across a wide optical spectral range from visible to far-infrared by synthetically varying doping level, and post synthetically via chemical oxidation and reduction, photochemical control, and electrochemical control. In this review, we will discuss the fundamental electromagnetic dynamics governing light matter interaction in plasmonic semiconductor NCs and the realization of various distinctive physical properties made possible by the advancement of colloidal synthesis routes to such NCs. Here, we will illustrate how free carrier dielectric properties are induced in various semiconductor materials including metal oxides, metal chalcogenides, metal nitrides, silicon, and other materials. We will highlight the applicability and limitations of the Drude model as applied to semiconductors considering the complex band structures and crystal structures that predominate and quantum effects that emerge at nonclassical sizes. We will also emphasize the impact of dopant hybridization with bands of the host lattice as well as the interplay of shape and crystal structure in determining the LSPR characteristics of semiconductor NCs. To illustrate the discussion regarding both physical and synthetic aspects of LSPR-active NCs, we will focus on metal oxides with substantial consideration also of copper chalcogenide NCs, with select examples drawn from the literature on other doped semiconductor materials. Furthermore, we will discuss the promise that LSPR in doped semiconductor NCs holds for a wide range of applications such as infrared spectroscopy, energy-saving technologies like smart windows and waste heat management, biomedical applications including therapy and imaging, and optical applications like two photon upconversion, enhanced luminesence, and infrared metasurfaces.

THiCweed: fast, sensitive detection of sequence features by clustering big datasets.

We present THiCweed, a new approach to analyzing transcription factor binding data from high-throughput chromatin immunoprecipitation-sequencing (ChIP-seq) experiments. THiCweed clusters bound regions based on sequence similarity using a divisive hierarchical clustering approach based on sequence similarity within sliding windows, while exploring both strands. ThiCweed is specially geared toward data containing mixtures of motifs, which present a challenge to traditional motif-finders. Our implementation is significantly faster than standard motif-finding programs, able to process 30 000 peaks in 1-2 h, on a single CPU core of a desktop computer. On synthetic data containing mixtures of motifs it is as accurate or more accurate than all other tested programs. THiCweed performs best with large 'window' sizes (≥50 bp), much longer than typical binding sites (7-15 bp). On real data it successfully recovers literature motifs, but also uncovers complex sequence characteristics in flanking DNA, variant motifs and secondary motifs even when they occur in <5% of the input, all of which appear biologically relevant. We also find recurring sequence patterns across diverse ChIP-seq datasets, possibly related to chromatin architecture and looping. THiCweed thus goes beyond traditional motif finding to give new insights into genomic transcription factor-binding complexity.

Competition between Depletion Effects and Coupling in the Plasmon Modulation of Doped Metal Oxide Nanocrystals.

Degenerately doped semiconductor nanocrystals (NCs) exhibit strong light-matter interactions due to localized surface plasmon resonance (LSPR) in the near- to mid-infrared region. Besides being readily tuned through dopant concentration introduced during synthesis, this LSPR can also be dynamically modulated by applying an external electrochemical potential. This characteristic makes these materials candidates for electrochromic window applications. Here, using prototypical doped indium oxide NCs as a model system, we find that the extent of electrochemical modulation of LSPR frequency is governed by the depletion width and the extent of inter-NC LSPR coupling, which are indirectly controlled by the dopant density, size, and packing density of the NCs. The depletion layer is a near-surface region with a sharply reduced free carrier population that occurs whenever the surface potential lies below the Fermi level. Changes in the depletion width under applied bias substantially control the spectral modulation of the LSPR of individual NCs and also modify the inter-NC LSPR coupling, which additionally modulates the LSPR absorption on the NC film scale. Here, we show that both of these effects must be considered primary factors in determining the extent of LSPR frequency modulation and that the dominant factor depends on NC size. For a constant doping concentration, depletion effects govern LSPR modulation for smaller NCs, while LSPR coupling is prevalent in larger NCs. Consequently, as the size of the NCs is increased while keeping the doping concentration constant, we observe a reversal in the sign of the LSPR frequency modulation from positive to negative.

Impacts of surface depletion on the plasmonic properties of doped semiconductor nanocrystals.

Degenerately doped semiconductor nanocrystals (NCs) exhibit a localized surface plasmon resonance (LSPR) in the infrared range of the electromagnetic spectrum. Unlike metals, semiconductor NCs offer tunable LSPR characteristics enabled by doping, or via electrochemical or photochemical charging. Tuning plasmonic properties through carrier density modulation suggests potential applications in smart optoelectronics, catalysis and sensing. Here, we elucidate fundamental aspects of LSPR modulation through dynamic carrier density tuning in Sn-doped In2O3 (Sn:In2O3) NCs. Monodisperse Sn:In2O3 NCs with various doping levels and sizes were synthesized and assembled in uniform films. NC films were then charged in an in situ electrochemical cell and the LSPR modulation spectra were monitored. Based on spectral shifts and intensity modulation of the LSPR, combined with optical modelling, it was found that often-neglected semiconductor properties, specifically band structure modification due to doping and surface states, strongly affect LSPR modulation. Fermi level pinning by surface defect states creates a surface depletion layer that alters the LSPR properties; it determines the extent of LSPR frequency modulation, diminishes the expected near-field enhancement, and strongly reduces sensitivity of the LSPR to the surroundings.