Novel and Advanced Ultrasound Techniques for Thyroid Thermal Ablation.

Thyroid radiofrequency ablation and microwave ablation are widely adopted minimally invasive treatments for diverse thyroid conditions worldwide. Fundamental skills such as the trans-isthmic approach and the moving shot technique are crucial for performing thyroid ablation, and advanced techniques, including hydrodissection and vascular ablation, improve safety and efficacy and reduce complications. Given the learning curve associated with ultrasound-guided therapeutic procedures, operators need training and experience. While training models exist, limited attention has been given to ultrasound maneuvers in ablation needle manipulation. This article introduces two essential maneuvers, the zigzag moving technique and the alienate maneuver, while also reviewing the latest ultrasound techniques in thyroid ablation, contributing valuable insights into this evolving field.

Modeling SARS-CoV-2 nucleotide mutations as a stochastic process.

This study analyzes the SARS-CoV-2 genome sequence mutations by modeling its nucleotide mutations as a stochastic process in both the time-series and spatial domain of the gene sequence. In the time-series model, a Markov Chain embedded Poisson random process characterizes the mutation rate matrix, while the spatial gene sequence model delineates the distribution of mutation inter-occurrence distances. Our experiment focuses on five key variants of concern that had become a global concern due to their high transmissibility and virulence. The time-series results reveal distinct asymmetries in mutation rate and propensities among different nucleotides and across different strains, with a mean mutation rate of approximately 2 mutations per month. In particular, our spatial gene sequence results reveal some novel biological insights on the characteristic distribution of mutation inter-occurrence distances, which display a notable pattern similar to other natural diseases. Our findings contribute interesting insights to the underlying biological mechanism of SARS-CoV-2 mutations, bringing us one step closer to improving the accuracy of existing mutation prediction models. This research could also potentially pave the way for future work in adopting similar spatial random process models and advanced spatial pattern recognition algorithms in order to characterize mutations on other different kinds of virus families.

In vivo stabilization of a less toxic asparaginase variant leads to a durable antitumor response in acute leukemia.

Asparagine is a non-essential amino acid since it can either be taken up via the diet or synthesized by asparagine synthetase. Acute lymphoblastic leukemia (ALL) cells do not express asparagine synthetase or express it only minimally, which makes them completely dependent on extracellular asparagine for their growth and survival. This dependency makes ALL cells vulnerable to treatment with L-asparaginase, an enzyme that hydrolyzes asparagine. To date, all clinically approved L-asparaginases have significant L-glutaminase co-activity, associated with non-immune related toxic side effects observed during therapy. Therefore, reduction of L-glutaminase co-activity with concomitant maintenance of its anticancer L-asparaginase effect may effectively improve the tolerability of this unique drug. Previously, we designed a new alternative variant of Erwinia chrysanthemi (ErA; Erwinaze) with decreased L-glutaminase co-activity, while maintaining its L-asparaginase activity, by the introduction of three key mutations around the active site (ErA-TM). However, Erwinaze and our ErA-TM variant have very short half-lives in vivo. Here, we show that the fusion of ErA-TM with an albumin binding domain (ABD)-tag significantly increases its in vivo persistence. In addition, we evaluated the in vivo therapeutic efficacy of ABD-ErA-TM in a B-ALL xenograft model of SUP-B15. Our results show a comparable long-lasting durable antileukemic effect between the standard-of-care pegylated-asparaginase and ABD-ErA-TM L-asparaginase, but with fewer co-glutaminase-related acute side effects. Since the toxic side effects of current L-asparaginases often result in treatment discontinuation in ALL patients, this novel ErA-TM variant with ultra-low L-glutaminase co-activity and long in vivo persistence may have great clinical potential.

Neural Causal Information Extractor for Unobserved Causes.

Causal inference aims to faithfully depict the causal relationships between given variables. However, in many practical systems, variables are often partially observed, and some unobserved variables could carry significant information and induce causal effects on a target. Identifying these unobserved causes remains a challenge, and existing works have not considered extracting the unobserved causes while retaining the causes that have already been observed and included. In this work, we aim to construct the implicit variables with a generator-discriminator framework named the Neural Causal Information Extractor (NCIE), which can complement the information of unobserved causes and thus provide a complete set of causes with both observed causes and the representations of unobserved causes. By maximizing the mutual information between the targets and the union of observed causes and implicit variables, the implicit variables we generate could complement the information that the unobserved causes should have provided. The synthetic experiments show that the implicit variables preserve the information and dynamics of the unobserved causes. In addition, extensive real-world time series prediction tasks show improved precision after introducing implicit variables, thus indicating their causality to the targets.

Tumoral microenvironment prevents de novo asparagine biosynthesis in B cell lymphoma, regardless of ASNS expression.

Depletion of circulating asparagine with l-asparaginase (ASNase) is a mainstay of leukemia treatment and is under investigation in many cancers. Expression levels of asparagine synthetase (ASNS), which catalyzes asparagine synthesis, were considered predictive of cancer cell sensitivity to ASNase treatment, a notion recently challenged. Using [U-13C5]-l-glutamine in vitro and in vivo in a mouse model of B cell lymphomas (BCLs), we demonstrated that supraphysiological or physiological concentrations of asparagine prevent de novo asparagine biosynthesis, regardless of ASNS expression levels. Overexpressing ASNS in ASNase-sensitive BCL was insufficient to confer resistance to ASNase treatment in vivo. Moreover, we showed that ASNase's glutaminase activity enables its maximal anticancer effect. Together, our results indicate that baseline ASNS expression (low or high) cannot dictate BCL dependence on de novo asparagine biosynthesis and predict BCL sensitivity to dual ASNase activity. Thus, except for ASNS-deficient cancer cells, ASNase's glutaminase activity should be considered in the clinic.

Successful Applications of Food-Assisted and -Simulated Training Model of Thyroid Radiofrequency Ablation.

Background: Radiofrequency ablation (RFA) for benign thyroid nodules is one kind of scarless treatment for symptomatic or cosmetic benign thyroid nodules. However, how to train RFA-naive physicians to become qualified operators for thyroid RFA is an important issue. Our study aimed to introduce a successful training model of thyroid RFA. Materials and Methods: We used a food-assisted and -simulated training model of thyroid RFA. Chicken hearts were simulated into thyroid nodules, three-layer pork meats were simulated into peri-thyroid structure, and gel bottles were simulated into trachea, respectively. Successful training ablations were defined as chicken hearts that were fully cooked. After repeating training ablations of chicken hearts at least 100 times with the nearly 100% success rates for three young trainees, they served as the first assistant for the real procedures of thyroid RFA and then were qualified to perform thyroid RFA on real patients under the supervision of one experienced interventional radiologist. Results: 23 real patients who received RFA and follow-up at least 6 months after treatment were included in Linkou Chang Gung Memorial Hospital from January 1, 2020 to October 1, 2021. Three young endocrinologists performed thyroid RFA independently. The outcomes were volume reduction rate (VRR), major complications and minor complications. The median VRR at 12 months was 82.00%, two major complications were transient hoarseness, and three minor complications were wound pain. All complications were completely recovered within three days. Conclusions: For young and RFA-native physicians without any basic skills of echo-guided intervention, this food-assisted and -simulated training model of thyroid RFA was useful for medical training and education.

Neural Network Structure Optimization by Simulated Annealing.

A critical problem in large neural networks is over parameterization with a large number of weight parameters, which limits their use on edge devices due to prohibitive computational power and memory/storage requirements. To make neural networks more practical on edge devices and real-time industrial applications, they need to be compressed in advance. Since edge devices cannot train or access trained networks when internet resources are scarce, the preloading of smaller networks is essential. Various works in the literature have shown that the redundant branches can be pruned strategically in a fully connected network without sacrificing the performance significantly. However, majority of these methodologies need high computational resources to integrate weight training via the back-propagation algorithm during the process of network compression. In this work, we draw attention to the optimization of the network structure for preserving performance despite compression by pruning aggressively. The structure optimization is performed using the simulated annealing algorithm only, without utilizing back-propagation for branch weight training. Being a heuristic-based, non-convex optimization method, simulated annealing provides a globally near-optimal solution to this NP-hard problem for a given percentage of branch pruning. Our simulation results have shown that simulated annealing can significantly reduce the complexity of a fully connected network while maintaining the performance without the help of back-propagation.

Crash Diagnosis and Price Rebound Prediction in NYSE Composite Index Based on Visibility Graph and Time-Evolving Stock Correlation Network.

This study proposes a framework to diagnose stock market crashes and predict the subsequent price rebounds. Based on the observation of anomalous changes in stock correlation networks during market crashes, we extend the log-periodic power-law model with a metric that is proposed to measure network anomalies. To calculate this metric, we design a prediction-guided anomaly detection algorithm based on the extreme value theory. Finally, we proposed a hybrid indicator to predict price rebounds of the stock index by combining the network anomaly metric and the visibility graph-based log-periodic power-law model. Experiments are conducted based on the New York Stock Exchange Composite Index from 4 January 1991 to 7 May 2021. It is shown that our proposed method outperforms the benchmark log-periodic power-law model on detecting the 12 major crashes and predicting the subsequent price rebounds by reducing the false alarm rate. This study sheds light on combining stock network analysis and financial time series modeling and highlights that anomalous changes of a stock network can be important criteria for detecting crashes and predicting recoveries of the stock market.

Using Deep Convolutional Neural Networks for Enhanced Ultrasonographic Image Diagnosis of Differentiated Thyroid Cancer.

Differentiated thyroid cancer (DTC) from follicular epithelial cells is the most common form of thyroid cancer. Beyond the common papillary thyroid carcinoma (PTC), there are a number of rare but difficult-to-diagnose pathological classifications, such as follicular thyroid carcinoma (FTC). We employed deep convolutional neural networks (CNNs) to facilitate the clinical diagnosis of differentiated thyroid cancers. An image dataset with thyroid ultrasound images of 421 DTCs and 391 benign patients was collected. Three CNNs (InceptionV3, ResNet101, and VGG19) were retrained and tested after undergoing transfer learning to classify malignant and benign thyroid tumors. The enrolled cases were classified as PTC, FTC, follicular variant of PTC (FVPTC), Hürthle cell carcinoma (HCC), or benign. The accuracy of the CNNs was as follows: InceptionV3 (76.5%), ResNet101 (77.6%), and VGG19 (76.1%). The sensitivity was as follows: InceptionV3 (83.7%), ResNet101 (72.5%), and VGG19 (66.2%). The specificity was as follows: InceptionV3 (83.7%), ResNet101 (81.4%), and VGG19 (76.9%). The area under the curve was as follows: Incep-tionV3 (0.82), ResNet101 (0.83), and VGG19 (0.83). A comparison between performance of physicians and CNNs was assessed and showed significantly better outcomes in the latter. Our results demonstrate that retrained deep CNNs can enhance diagnostic accuracy in most DTCs, including follicular cancers.

Revealing the Photophysical Dynamics of Selected Rigid Donor-Acceptor Systems: From Ligands to Ruthenium(II) Complexes.

Newly designed push-pull ligands (L1 and L2) with bithiophene (bth) as a donor and phenazine (phz) or quinoxalino[2,3-b]quinoxaline (qxq) as acceptors were synthesized and also incorporated with a bipyridyl Ru(II) complex to give Ru1 and Ru2, respectively. The ultrafast photophysical dynamics of the ligand and their respective Ru(II) complexes were well-characterized using time-resolved spectroscopies and quantum chemical calculations. Photoinduced charger transfer (CT) and intersystem crossing (ISC) processes were directly observed for L1 and L2. In addition, the interplay of three different triplet excited states was directly observed in the related Ru(II) complexes. The lowest-lying triplet excited states of the ligands and their respective Ru(II) complexes were both attributed to the CT transitions from donor (bth) to acceptor (phz or qxq) and result in 3ICT (intramolecular charge transfer) and 3ILCT (intraligand charge transfer) excited states, respectively. The lifetimes of the lowest-lying triplet excited states of L1, L2, Ru1, and Ru2 were measured to be 21.3, 50.4, 2.75, and 4.16 µs, respectively.

Targeting MYC-enhanced glycolysis for the treatment of small cell lung cancer.

INTRODUCTION: The transcription factor MYC is overexpressed in 30% of small cell lung cancer (SCLC) tumors and is known to modulate the balance between two major pathways of metabolism: glycolysis and mitochondrial respiration. This duality of MYC underscores the importance of further investigation into its role in SCLC metabolism and could lead to insights into metabolic targeting approaches. METHODS: We investigated differences in metabolic pathways in transcriptional and metabolomics datasets based on cMYC expression in patient and cell line samples. Metabolic pathway utilization was evaluated by flow cytometry and Seahorse extracellular flux methodology. Glycolysis inhibition was evaluated in vitro and in vivo using PFK158, a small molecular inhibitor of PFKFB3. RESULTS: MYC-overexpressing SCLC patient samples and cell lines exhibited increased glycolysis gene expression directly mediated by MYC. Further, MYC-overexpressing cell lines displayed enhanced glycolysis consistent with the Warburg effect, while cell lines with low MYC expression appeared more reliant on oxidative metabolism. Inhibition of glycolysis with PFK158 preferentially attenuated glucose uptake, ATP production, and lactate in MYC-overexpressing cell lines. Treatment with PFK158 in xenografts delayed tumor growth and decreased glycolysis gene expression. CONCLUSIONS: Our study highlights an in-depth characterization of SCLC metabolic programming and presents glycolysis as a targetable mechanism downstream of MYC that could offer therapeutic benefit in a subset of SCLC patients.

PGC1α is required for the renoprotective effect of lncRNA Tug1 in vivo and links Tug1 with urea cycle metabolites.

lncRNA taurine-upregulated gene 1 (Tug1) is a promising therapeutic target in the progression of diabetic nephropathy (DN), but the molecular basis of its protection remains poorly understood. Here, we generate a triple-mutant diabetic mouse model coupled with metabolomic profiling data to interrogate whether Tug1 interaction with peroxisome proliferator-activated receptor gamma coactivator 1α (PGC1α) is required for mitochondrial remodeling and progression of DN in vivo. We find that, compared with diabetic conditional deletion of Pgc1α in podocytes alone (db/db; Pgc1αPod-f/f), diabetic Pgc1α knockout combined with podocyte-specific Tug1 overexpression (db/db; TugPodTg; Pgc1αPod-f/f) reverses the protective phenotype of Tug1 overexpression, suggesting that PGC1α is required for the renoprotective effect of Tug1. Using unbiased metabolomic profiling, we find that altered urea cycle metabolites and mitochondrial arginase 2 play an important role in Tug1/PGC1α-induced mitochondrial remodeling. Our work identifies a functional role of the Tug1/PGC1α axis on mitochondrial metabolic homeostasis and urea cycle metabolites in experimental models of diabetes.

Association between serum bilirubin levels and progression of albuminuria in Taiwanese with type 2 diabetes mellitus.

BACKGROUND: To investigate the association between serum bilirubin (BIL) levels and the progression of albuminuria in type 2 diabetic Taiwanese. METHODS: Longitudinal data from January 2001 to June 2015 were retrospectively reviewed from Chang Gung Memorial Hospital in Taiwan. A total of 2877 type 2 diabetic patients with normal total BIL levels were divided into 4 groups according to BIL, with the highest BIL in the fourth group. The urinary albumin/creatinine ratio (UACR) trend and progression, as well as other laboratory measurements, were evaluated among the four groups. The cumulative incidence and Cox proportional hazard model analysis were performed to examine the relationship between BIL and the risk of albuminuria progression (AUPr). RESULTS: The mean duration of follow-up was 1.5 years (±1.37 years). The mean patient age, glycosylated hemoglobin level, and duration of diabetes were 62.52 years, 7.9%, and 3.94 years, respectively. A significant correlation was observed between BIL and both the UACR at baseline (P < 0.001) and the cumulative incidence of AUPr (log-rank test, P = 0.031). Hazard ratio (HR) analysis revealed that patients in the fourth BIL quartile had the lowest HR risk of AUPr among the four groups (adjusted HR = 0.70; 95% Confidence Interval = 0.56-0.89, P < 0.05). CONCLUSIONS: Higher serum BIL levels are associated with a lower risk of AUPr in type 2 diabetes patients in Taiwan.

Mechanism of Catalysis by l-Asparaginase.

Two bacterial type II l-asparaginases, from Escherichia coli and Dickeya chrysanthemi, have played a critical role for more than 40 years as therapeutic agents against juvenile leukemias and lymphomas. Despite a long history of successful pharmacological applications and the apparent simplicity of the catalytic reaction, controversies still exist regarding major steps of the mechanism. In this report, we provide a detailed description of the reaction catalyzed by E. coli type II l-asparaginase (EcAII). Our model was developed on the basis of new structural and biochemical experiments combined with previously published data. The proposed mechanism is supported by quantum chemistry calculations based on density functional theory. We provide strong evidence that EcAII catalyzes the reaction according to the double-displacement (ping-pong) mechanism, with formation of a covalent intermediate. Several steps of catalysis by EcAII are unique when compared to reactions catalyzed by other known hydrolytic enzymes. Here, the reaction is initiated by a weak nucleophile, threonine, without direct assistance of a general base, although a distant general base is identified. Furthermore, tetrahedral intermediates formed during the catalytic process are stabilized by a never previously described motif. Although the scheme of the catalytic mechanism was developed only on the basis of data obtained from EcAII and its variants, this novel mechanism of enzymatic hydrolysis could potentially apply to most (and possibly all) l-asparaginases.

Synthesis of Pyrazinopyrazine-Fused Azaacenes through Direct Condensation Reactions between Quinoxalinediamine and Diketones.

We report the synthesis of a new type of pyrazinopyrazine-fused azaacene molecules by a simple and versatile procedure. 6,9-Dihexyldithieno[3,2-f:2',3'-h]quinoxaline-2,3-diamine was synthesized through the condensation between 2,7-dihexylbenzo[1,2-b:6,5-b']dithiophene-4,5-diamine and bis(2,2,2-trifluoroethyl) oximidate. A series of derivatized molecules with extended two-dimensional aromatic fused-ring structures could be obtained by simple condensation reactions between the quinoxalinediamine intermediate and various diketones. The reaction was proved to be effective for the construction of tetrazaacene derivatives with extended heterocyclic aromatic ring systems. The molecules obtained exhibit low-lying LUMO levels that can be fine-tuned by modifying the molecular structure. Crystallographic results showed that in a solid state, the molecules form "brick wall" structures with a close π-π stacking mode. The stacking between the π-ring systems in the molecules could be further enhanced by expanding the large 2D planar-conjugated structure.

Glutaminase Activity of L-Asparaginase Contributes to Durable Preclinical Activity against Acute Lymphoblastic Leukemia.

We and others have reported that the anticancer activity of L-asparaginase (ASNase) against asparagine synthetase (ASNS)-positive cell types requires ASNase glutaminase activity, whereas anticancer activity against ASNS-negative cell types does not. Here, we attempted to disentangle the relationship between asparagine metabolism, glutamine metabolism, and downstream pathways that modulate cell viability by testing the hypothesis that ASNase anticancer activity is based on asparagine depletion rather than glutamine depletion per se. We tested ASNase wild-type (ASNaseWT) and its glutaminase-deficient Q59L mutant (ASNaseQ59L) and found that ASNase glutaminase activity contributed to durable anticancer activity against xenografts of the ASNS-negative Sup-B15 leukemia cell line in NOD/SCID gamma mice, whereas asparaginase activity alone yielded a mere growth delay. Our findings suggest that ASNase glutaminase activity is necessary for durable, single-agent anticancer activity in vivo, even against ASNS-negative cancer types.

Response envelope analysis for quantitative evaluation of drug combinations.

MOTIVATION: The concept of synergy between two agents, over a century old, is important to the fields of biology, chemistry, pharmacology and medicine. A key step in drug combination analysis is the selection of an additivity model to identify combination effects including synergy, additivity and antagonism. Existing methods for identifying and interpreting those combination effects have limitations. RESULTS: We present here a computational framework, termed response envelope analysis (REA), that makes use of 3D response surfaces formed by generalized Loewe Additivity and Bliss Independence models of interaction to evaluate drug combination effects. Because the two models imply two extreme limits of drug interaction (mutually exclusive and mutually non-exclusive), a response envelope defined by them provides a quantitatively stringent additivity model for identifying combination effects without knowing the inhibition mechanism. As a demonstration, we apply REA to representative published data from large screens of anticancer and antibiotic combinations. We show that REA is more accurate than existing methods and provides more consistent results in the context of cross-experiment evaluation. AVAILABILITY AND IMPLEMENTATION: The open-source software package associated with REA is available at: https://github.com/4dsoftware/rea. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Enteral Activation of WR-2721 Mediates Radioprotection and Improved Survival from Lethal Fractionated Radiation.

Unresectable pancreatic cancer is almost universally lethal because chemotherapy and radiation cannot completely stop the growth of the cancer. The major problem with using radiation to approximate surgery in unresectable disease is that the radiation dose required to ablate pancreatic cancer exceeds the tolerance of the nearby duodenum. WR-2721, also known as amifostine, is a well-known radioprotector, but has significant clinical toxicities when given systemically. WR-2721 is a prodrug and is converted to its active metabolite, WR-1065, by alkaline phosphatases in normal tissues. The small intestine is highly enriched in these activating enzymes, and thus we reasoned that oral administration of WR-2721 just before radiation would result in localized production of the radioprotective WR-1065 in the small intestine, providing protective benefits without the significant systemic side effects. Here, we show that oral WR-2721 is as effective as intraperitoneal WR-2721 in promoting survival of intestinal crypt clonogens after morbid irradiation. Furthermore, oral WR-2721 confers full radioprotection and survival after lethal upper abdominal irradiation of 12.5 Gy × 5 fractions (total of 62.5 Gy, EQD2 = 140.6 Gy). This radioprotection enables ablative radiation therapy in a mouse model of pancreatic cancer and nearly triples the median survival compared to controls. We find that the efficacy of oral WR-2721 stems from its selective accumulation in the intestine, but not in tumors or other normal tissues, as determined by in vivo mass spectrometry analysis. Thus, we demonstrate that oral WR-2721 is a well-tolerated, and quantitatively selective, radioprotector of the intestinal tract that is capable of enabling clinically relevant ablative doses of radiation to the upper abdomen without unacceptable gastrointestinal toxicity.

Assessment of l-Asparaginase Pharmacodynamics in Mouse Models of Cancer.

l-asparaginase (ASNase) is a metabolism-targeted anti-neoplastic agent used to treat acute lymphoblastic leukemia (ALL). ASNase's anticancer activity results from the enzymatic depletion of asparagine (Asn) and glutamine (Gln), which are converted to aspartic acid (Asp) and glutamic acid (Glu), respectively, in the blood. Unfortunately, accurate assessment of the in vivo pharmacodynamics (PD) of ASNase is challenging because of the following reasons: (i) ASNase is resilient to deactivation; (ii) ASNase catalytic efficiency is very high; and (iii) the PD markers Asn and Gln are depleted ex vivo in blood samples containing ASNase. To address those issues and facilitate longitudinal studies in individual mice for ASNase PD studies, we present here a new LC-MS/MS bioanalytical method that incorporates rapid quenching of ASNase for measurement of Asn, Asp, Gln, and Glu in just 10 µL of whole blood, with limits of detection (s:n ≥ 10:1) estimated to be 2.3, 3.5, 0.8, and 0.5 µM, respectively. We tested the suitability of the method in a 5-day, longitudinal PD study in mice and found the method to be simple to perform with sufficient accuracy and precision for whole blood measurements. Overall, the method increases the density of data that can be acquired from a single animal and will facilitate optimization of novel ASNase treatment regimens and/or the development of new ASNase variants with desired kinetic properties.

Control of Electron Flow Direction in Photoexcited Cycloplatinated Complex Containing Conjugated Polymer-Single-Walled Carbon Nanotube Hybrids.

Conjugated polymers incorporated with cycloplatinated complexes (P1-Pt and P2-Pt) were used as dispersants for single-walled carbon nanotubes (SWCNTs). Significant changes in the UV-vis absorption spectra were observed after the formation of the polymer/SWCNT hybrids. Molecular dynamics (MD) simulations revealed the presence of a strong interaction between the cycloplatinated complex moieties and the SWCNT surface. The photoinduced electron transfer processes in these hybrids were strongly dependent on the type of the comonomer unit. Upon photoexcitation, the excited P1-Pt donates electrons to the SWCNT, while P2-Pt accepts electrons from the photoexcited SWCNT. These observations were supported by results from Raman and femtosecond time-resolved transient absorption spectroscopy experiments. The strong electronic interaction between the Pt complexes and the SWCNT gives rise to a new hybrid system that has a controllable photoinduced electron transfer flow, which are important in regulating the charge transport processes in SWCNT-based optoelectronic devices.