Laparoscopic management of a giant adrenal cyst

AbstractAdrenal cysts, a rare entity, are usually nonfunctional and asymptomatic. Here, we report a 32-year-old woman who presented with mild breathlessness and vague abdominal fullness and discomfort that had lasted 6 months. Chest radiography showed elevation of the left side of the diaphragm. Abdominal sonography showed an anechoic lesion of >15cm, without a septum, that was situated over the left abdominal area. Abdominal computed tomography (CT) showed a 20cm suprarenal cyst located between the pancreas, spleen, and left kidney, causing anterior displacement of the pancreas and inferior displacement of the left kidney. Magnetic resonance imaging confirmed the CT and sonographic findings, and revealed that the cystic mass was originating from the left adrenal gland. Fluid analysis of the cystic lesion showed no evidence of infection or malignancy. A laparoscopic adrenalectomy was performed. Histopathologically, the adrenal tissue showed no evidence of adenoma or malignancy, and the cystic component showed a flattened endothelial lining with fibrotic tissue, consistent with an endothelial cyst. The postoperative course was uneventful and the patient had no evidence of recurrence during a 6-year follow-up. We discuss the diagnosis and management of adrenal cysts

One-step Multi-view Clustering with Diverse Representation

Multi-view clustering has attracted broad attention due to its capacity to utilize consistent and complementary information among views. Although tremendous progress has been made recently, most existing methods undergo high complexity, preventing them from being applied to large-scale tasks. Multi-view clustering via matrix factorization is a representative to address this issue. However, most of them map the data matrices into a fixed dimension, which limits the expressiveness of the model. Moreover, a range of methods suffer from a two-step process, i.e., multimodal learning and the subsequent $k$-means, inevitably causing a sub-optimal clustering result. In light of this, we propose a one-step multi-view clustering with diverse representation method, which incorporates multi-view learning and $k$-means into a unified framework. Specifically, we first project original data matrices into various latent spaces to attain comprehensive information and auto-weight them in a self-supervised manner. Then we directly use the information matrices under diverse dimensions to obtain consensus discrete clustering labels. The unified work of representation learning and clustering boosts the quality of the final results. Furthermore, we develop an efficient optimization algorithm to solve the resultant problem with proven convergence. Comprehensive experiments on various datasets demonstrate the promising clustering performance of our proposed method

Hypophosphatemia during continuous veno-venous hemofiltration is associated with mortality in critically ill patients with acute kidney injury

INTRODUCTION: The primary aim of this study was to determine whether hypophosphatemia during continuous veno-venous hemofiltration (CVVH) is associated with the global outcome of critically ill patients with acute kidney injury (AKI). METHODS: 760 patients diagnosed with AKI and had received CVVH therapy were retrospectively recruited. Death during the 28-day period and survival at 28 days after initiation of CVVH were used as endpoints. Demographic and clinical data including serum phosphorus levels were recorded along with clinical outcome. Hypophosphatemia was defined according to the colorimetric method as serum phosphorus levels < 0.81 mmol/L (2.5 mg/dL), and severe hypophosphatemia was defined as serum phosphorus levels < 0.32 mmol/L (1 mg/dL). The ratio of CVVH therapy days with hypophosphatemia over total CVVH therapy days was calculated to reflect the persistence of hypophosphatemia. RESULTS: The Cox proportional hazard survival model analysis indicated that the incidence of hypophosphatemia or even severe hypophosphatemia was not associated with 28-day mortality independently (p = 0.700). Further analysis with the sub-cohort of patients who had developed hypophosphatemia during the CVVH therapy period indicated that the mean ratio of CVVH therapy days with hypophosphatemia over total CVVH therapy days was 0.58, and the ratio independently associated with the global outcome. Compared with the patients with low ratio (< 0.58), those with high ratio (≥ 0.58) conferred a 1.451-fold increase in 28-day mortality rate (95% CI 1.103–1.910, p = 0.008). CONCLUSIONS: Hypophosphatemia during CVVH associated with the global clinical outcome of critically ill patients with AKI. The ratio of CVVH therapy days with hypophosphatemia over total CVVH therapy days was independently associated with the 28-day mortality, and high ratio conferred higher mortality rate

Differential contributory roles of nucleotide excision and homologous recombination repair for enhancing cisplatin sensitivity in human ovarian cancer cells

<p>Abstract</p> <p>Background</p> <p>While platinum-based chemotherapeutic agents are widely used to treat various solid tumors, the acquired platinum resistance is a major impediment in their successful treatment. Since enhanced DNA repair capacity is a major factor in conferring cisplatin resistance, targeting of DNA repair pathways is an effective stratagem for overcoming cisplatin resistance. This study was designed to delineate the role of nucleotide excision repair (NER), the principal mechanism for the removal of cisplatin-induced DNA intrastrand crosslinks, in cisplatin resistance and reveal the impact of DNA repair interference on cisplatin sensitivity in human ovarian cancer cells.</p> <p>Results</p> <p>We assessed the inherent NER efficiency of multiple matched pairs of cisplatin-sensitive and -resistant ovarian cancer cell lines and their expression of NER-related factors at mRNA and protein levels. Our results showed that only the cisplatin-resistant ovarian cancer cell line PEO4 possessed an increased NER capacity compared to its inherently NER-inefficient parental line PEO1. Several other cisplatin-resistant cell lines, including CP70, CDDP and 2008C13, exhibited a normal and parental cell-comparable NER capacity for removing cisplatin-induced DNA intrastrand cross-links (Pt-GG). Concomitant gene expression analysis revealed discordance in mRNA and protein levels of NER factors in various ovarian cancer cell lines and NER proteins level were unrelated to the cisplatin sensitivity of these cell lines. Although knockdown of NER factors was able to compromise the NER efficiency, it only caused a minimal effect on cisplatin sensitivity. On the contrary, downregulation of BRCA2, a critical protein for homologous recombination repair (HRR), significantly enhanced the efficacy of cisplatin in killing ovarian cancer cell line PEO4.</p> <p>Conclusion</p> <p>Our studies indicate that the level of NER factors in ovarian cancer cell lines is neither a determinant of their NER capacity nor of the sensitivity to cisplatin, and suggest that manipulation of the HRR but not the NER factor expression provides an effective strategy for sensitizing cisplatin-resistant tumors to platinating agents.</p

Genomic Inference of the Metabolism and Evolution of the Archaeal Phylum Aigarchaeota

Microbes of the phylum Aigarchaeota are widely distributed in geothermal environments, but their physiological and ecological roles are poorly understood. Here we analyze six Aigarchaeota metagenomic bins from two circumneutral hot springs in Tengchong, China, to reveal that they are either strict or facultative anaerobes, and most are chemolithotrophs that can perform sulfide oxidation. Applying comparative genomics to the Thaumarchaeota and Aigarchaeota, we find that they both originated from thermal habitats, sharing 1154 genes with their common ancestor. Horizontal gene transfer played a crucial role in shaping genetic diversity of Aigarchaeota and led to functional partitioning and ecological divergence among sympatric microbes, as several key functional innovations were endowed by Bacteria, including dissimilatory sulfite reduction and possibly carbon monoxide oxidation. Our study expands our knowledge of the possible ecological roles of the Aigarchaeota and clarifies their evolutionary relationship to their sister lineage Thaumarchaeota

Scalable Incomplete Multi-View Clustering with Structure Alignment

The success of existing multi-view clustering (MVC) relies on the assumption that all views are complete. However, samples are usually partially available due to data corruption or sensor malfunction, which raises the research of incomplete multi-view clustering (IMVC). Although several anchor-based IMVC methods have been proposed to process the large-scale incomplete data, they still suffer from the following drawbacks: i) Most existing approaches neglect the inter-view discrepancy and enforce cross-view representation to be consistent, which would corrupt the representation capability of the model; ii) Due to the samples disparity between different views, the learned anchor might be misaligned, which we referred as the Anchor-Unaligned Problem for Incomplete data (AUP-ID). Such the AUP-ID would cause inaccurate graph fusion and degrades clustering performance. To tackle these issues, we propose a novel incomplete anchor graph learning framework termed Scalable Incomplete Multi-View Clustering with Structure Alignment (SIMVC-SA). Specially, we construct the view-specific anchor graph to capture the complementary information from different views. In order to solve the AUP-ID, we propose a novel structure alignment module to refine the cross-view anchor correspondence. Meanwhile, the anchor graph construction and alignment are jointly optimized in our unified framework to enhance clustering quality. Through anchor graph construction instead of full graphs, the time and space complexity of the proposed SIMVC-SA is proven to be linearly correlated with the number of samples. Extensive experiments on seven incomplete benchmark datasets demonstrate the effectiveness and efficiency of our proposed method. Our code is publicly available at https://github.com/wy1019/SIMVC-SA

Augmenting recombinant antibody production in HEK293E cells: Optimizing transfection and culture parameters

Background: Optimizing recombinant antibody production is important for cost-effective therapeutics and diagnostics. With impact on commercialization, higher productivity beyond laboratory scales is highly sought, where efficient production can also accelerate antibody characterizations and investigations. Methods: Investigating HEK293E cells for mammalian antibody production, various transfection and culture parameters were systematically analyzed for antibody light chain production before evaluating them for whole antibody production. Transfection parameters investigated include seeding cell density, the concentration of the transfection reagent and DNA, complexation time, temperature, and volume, as well as culture parameters such as medium replacement, serum deprivation, use of cell maintenance antibiotic, incubation temperature, medium volume, post-transfection harvest day, and common nutrient supplements. Results: Using 2 mL adherent HEK293E cell culture transfections with 25 kDa linear polyethylenimine in the most optimized parameters, we demonstrated a ~2-fold production increase for light chain alone and for whole antibody production reaching 536 and 49 μg, respectively, in a cost-effective manner. With the addition of peptone, κ light chain increased by ~4-fold to 1032 μg, whereas whole antibody increased to a lesser extent by ~2.5-fold to 51 μg, with benefits potentially for antibodies limited by their light chains in production. Conclusions: Our optimized findings show promise for a more efficient and convenient antibody production method through transfection and culture optimizations that can be incorporated to scale-up processes and with potential transferability to other mammalian-based recombinant protein production using HEK293E

DealMVC: Dual Contrastive Calibration for Multi-view Clustering

Benefiting from the strong view-consistent information mining capacity, multi-view contrastive clustering has attracted plenty of attention in recent years. However, we observe the following drawback, which limits the clustering performance from further improvement. The existing multi-view models mainly focus on the consistency of the same samples in different views while ignoring the circumstance of similar but different samples in cross-view scenarios. To solve this problem, we propose a novel Dual contrastive calibration network for Multi-View Clustering (DealMVC). Specifically, we first design a fusion mechanism to obtain a global cross-view feature. Then, a global contrastive calibration loss is proposed by aligning the view feature similarity graph and the high-confidence pseudo-label graph. Moreover, to utilize the diversity of multi-view information, we propose a local contrastive calibration loss to constrain the consistency of pair-wise view features. The feature structure is regularized by reliable class information, thus guaranteeing similar samples have similar features in different views. During the training procedure, the interacted cross-view feature is jointly optimized at both local and global levels. In comparison with other state-of-the-art approaches, the comprehensive experimental results obtained from eight benchmark datasets provide substantial validation of the effectiveness and superiority of our algorithm. We release the code of DealMVC at https://github.com/xihongyang1999/DealMVC on GitHub

A Channel to Form Fast-spinning Black Hole-Neutron Star Binary Mergers as Multimessenger Sources. II. Accretion-induced Spin-up

In this work, we investigate an alternative channel for the formation of fast-spinning black hole-neutron star (BHNS) binaries, in which super-Eddington accretion is expected to occur in accreting BHs during the stable mass transfer phase within BH-stripped helium (BH--He-rich) star binary systems. We evolve intensive \texttt{MESA} grids of close-orbit BH--He-rich star systems to systematically explore the projected aligned spins of BHs in BHNS binaries, as well as the impact of different accretion limits on the tidal disruption probability and electromagnetic (EM) signature of BHNS mergers. Most of the BHs in BHNS mergers cannot be effectively spun up through accretion, if the accretion rate is limited to $\lesssim10\,\dot{M}_{\rm Edd}$, where $\dot{M}_{\rm Edd}$ is the standard Eddington accretion limit. In order to reach high spins (e.g., $\chi_{\rm BH} \gtrsim 0.5$), the BHs are required to be born less massive (e.g., $\lesssim3.0\,M_\odot$) in binary systems with initial periods of $\lesssim0.2-0.3\,{\rm days}$ and accrete material at $\sim100\,\dot{M}_{\rm Edd}$. However, even under this high accretion limit, $\gtrsim6\,M_\odot$ BHs are typically challenging to significantly spin up and generate detectable associated EM signals. Our population simulations suggest that different accretion limits have a slight impact on the ratio of tidal disruption events. However, as the accretion limit increases, the EM counterparts from the cosmological BHNS population can become bright overall.Comment: 18 pages, 9 figures, 1 table, accepted for publication in Ap

Deep Learning-Enabled Swallowing Monitoring and Postoperative Recovery Biosensing System

This study introduces an innovative 3D printed dry electrode tailored for biosensing in postoperative recovery scenarios. Fabricated through a drop coating process, the electrode incorporates a novel 2D material.Comment: the abstract can't uploaded full