Effects of a comprehensive brain computed tomography deep learning model on radiologist detection accuracy.

OBJECTIVES: Non-contrast computed tomography of the brain (NCCTB) is commonly used to detect intracranial pathology but is subject to interpretation errors. Machine learning can augment clinical decision-making and improve NCCTB scan interpretation. This retrospective detection accuracy study assessed the performance of radiologists assisted by a deep learning model and compared the standalone performance of the model with that of unassisted radiologists. METHODS: A deep learning model was trained on 212,484 NCCTB scans drawn from a private radiology group in Australia. Scans from inpatient, outpatient, and emergency settings were included. Scan inclusion criteria were age ≥ 18 years and series slice thickness ≤ 1.5 mm. Thirty-two radiologists reviewed 2848 scans with and without the assistance of the deep learning system and rated their confidence in the presence of each finding using a 7-point scale. Differences in AUC and Matthews correlation coefficient (MCC) were calculated using a ground-truth gold standard. RESULTS: The model demonstrated an average area under the receiver operating characteristic curve (AUC) of 0.93 across 144 NCCTB findings and significantly improved radiologist interpretation performance. Assisted and unassisted radiologists demonstrated an average AUC of 0.79 and 0.73 across 22 grouped parent findings and 0.72 and 0.68 across 189 child findings, respectively. When assisted by the model, radiologist AUC was significantly improved for 91 findings (158 findings were non-inferior), and reading time was significantly reduced. CONCLUSIONS: The assistance of a comprehensive deep learning model significantly improved radiologist detection accuracy across a wide range of clinical findings and demonstrated the potential to improve NCCTB interpretation. CLINICAL RELEVANCE STATEMENT: This study evaluated a comprehensive CT brain deep learning model, which performed strongly, improved the performance of radiologists, and reduced interpretation time. The model may reduce errors, improve efficiency, facilitate triage, and better enable the delivery of timely patient care. KEY POINTS: • This study demonstrated that the use of a comprehensive deep learning system assisted radiologists in the detection of a wide range of abnormalities on non-contrast brain computed tomography scans. • The deep learning model demonstrated an average area under the receiver operating characteristic curve of 0.93 across 144 findings and significantly improved radiologist interpretation performance. • The assistance of the comprehensive deep learning model significantly reduced the time required for radiologists to interpret computed tomography scans of the brain.

Annona glabra L. Seeds: An Agricultural Waste Biosorbent for the Eco-Friendly Removal of Methylene Blue.

The seeds of Annona glabra L., an invasive plant in Vietnam, were first employed as a new biosorbent for the adsorption of methylene blue (MB) from aqueous media. The characterizations of the material using FT-IR, SEM, nitrogen adsorption-desorption analysis, and point of zero charge reveals that it possesses a rough and irregular surface, various polar functional groups, and pHpzc of 5.5. Certain adsorption conditions including adsorbent dose, solution pH, contact time, and initial concentration of MB were found to affect adsorption efficiency. The kinetic data are well fitted with pseudo-second-order model with the adsorption rate of 0.002 g mg-1 min-1 and initial rate of 4.46 mg g-1 min-1. For the adsorption isotherm, three nonlinear models were used to analyze the experiment data, including Langmuir, Freundlich, and Temkin. The results indicate that the Langmuir model best describes the adsorption of Annona glabra L. seeds powder (AGSP) with a maximum adsorption capacity of 98.0 mg g-1. The investigation underpins the adsorption mechanism, whereby the electrostatic attraction between positively charged MB and negatively charged surface of AGSP is expected to be the predominant mechanism, together with hydrogen bonding and pi-pi interaction. These results make AGSP an interesting biosorbent concerning its environmental friendliness, cost-effectiveness, and relatively high dye adsorption capacity.

Simulation Reveals the Chameleonic Behavior of Macrocycles.

Conformational analysis is central to the design of bioactive molecules. It is particularly challenging for macrocycles due to noncovalent transannular interactions, steric interactions, and ring strain that are often coupled. Herein, we simulated the conformations of five macrocycles designed to express a progression of increasing complexity in environment-dependent intramolecular interactions and verified the results against NMR measurements in chloroform and dimethyl sulfoxide. Molecular dynamics using an explicit solvent model, but not the Monte Carlo method with implicit solvation, handled both solvents correctly. Refinement of conformations at the ab initio level was fundamental to reproducing the experimental observations─standard state-of-the-art molecular mechanics force fields were insufficient. Our simulations correctly predicted the intramolecular interactions between side chains and the macrocycle and revealed an unprecedented solvent-induced conformational switch of the macrocyclic ring. Our results provide a platform for the rational, prospective design of molecular chameleons that adapt to the properties of the environment.

A Comparison of a Conventional Chemical Coagulant and a Natural Coagulant Derived from Cassia fistula Seeds for the Removal of Heavy Metal Ions.

Cassia fistula seed-derived coagulant has been reported to exhibit high coagulating-flocculating activity, environmental friendliness, and cost-effectiveness for the wastewater treatment, especially of textile wastewater. For heavy metal removal, however, research focusing on evaluating the feasibility of this material is still limited. Therefore, this study reports jar-test experiments in which the Zn2+ and Ni2+ removal efficiency of C. fistula coagulant was assessed. Moreover, a comparison of coagulation performance using a conventional chemical coagulant and the natural coagulant was performed. Characterization of the C. fistula seed-derived coagulant revealed the presence of important functional groups and fibrous networks with rough surfaces. A bench-scale study indicated that the coagulation performance of the two coagulants depends strongly on the initial concentration of metal ions, pH level, and coagulant dosage. The C. fistula seed-derived coagulant was found to possess higher removal efficiency than polyaluminum chloride. This natural coagulant removed over 80% of metal ions at the optimal conditions of pH 5.0, a metal ion concentration of 25 ppm, and a dosage of 0.8 and 1.6 g/L for Zn2+ and Ni2+, respectively. This study shows that C. fistula seed-derived coagulant is a potential alternative to chemical coagulants and could be developed to provide an environmentally friendly, economical, and efficient wastewater treatment.

Adopting the Swenson-like technique for patients with Hirschsprung disease in Vietnam.

PURPOSE: To evaluate outcomes of adopting the Swenson-like technique in transanal pull-through for Hirschsprung disease (HD) at a children's institution in Southeast Asia. METHODS: A retrospective chart review was performed over 42 months at a safety-net pediatric hospital in Vietnam. RESULTS: From January 2019 to June 2022, the Swenson-like technique was implemented and performed on 139 patients (115 male, 24 female, mean age 6.4 ± 11.96 months). There were 123 transanal-only resections, 5 transanal plus laparoscopic, and 11 transanal plus laparotomy. The mean operative time was 70.9 ± 43.6 min. The average length of the resected specimen was 18.8 ± 10.9 cm. No urethral or vaginal injuries occurred. Postoperative complications included 1 anastomotic leak (0.7%), 4 anastomotic stenoses (2.8%), and 2 perianal abscesses in the setting of recurrent enterocolitis (1.4%). With a mean follow-up of 26 ± 11.9 months (range 3-48 months), there were 25 enterocolitis cases (17.9%), 45 patients with constipation (32.3%), 1 episode of fecal incontinence lasting longer than 6 months (0.7%), and 1 rectal-vestibular fistula noted one year postoperatively (0.7%). There were no deaths. CONCLUSION: The Swenson-like technique in transanal pull-through for Hirschsprung's disease was safely adopted at our institution. The results show that applying this technique uniformly in a single institution led to excellent outcomes.

Design of Drug Efficacy Guided by Free Energy Simulations of the ß2 -Adrenoceptor.

G-protein-coupled receptors (GPCRs) play important roles in physiological processes and are modulated by drugs that either activate or block signaling. Rational design of the pharmacological efficacy profiles of GPCR ligands could enable the development of more efficient drugs, but is challenging even if high-resolution receptor structures are available. We performed molecular dynamics simulations of the ß2 adrenergic receptor in active and inactive conformations to assess if binding free energy calculations can predict differences in ligand efficacy for closely related compounds. Previously identified ligands were successfully classified into groups with comparable efficacy profiles based on the calculated shift in ligand affinity upon activation. A series of ligands were then predicted and synthesized, leading to the discovery of partial agonists with nanomolar potencies and novel scaffolds. Our results demonstrate that free energy simulations enable design of ligand efficacy and the same approach can be applied to other GPCR drug targets.

Elucidation of the nematicidal mode of action of grammicin on Caenorhabditis elegans.

Grammicin (Gra) is derived from the endophytic fungus Xylaria grammica EL000614 and shows nematicidal activity against the devastating root-knot nematode Meloidogyne incognita in-vitro, in planta, and in-field experiments. However, the mechanism of the nematicidal action of Gra remains unclear. In this study, Gra exposure to the model genetic organism Caenorhabditis elegans affected its L1, L2/3, L4, and young adult stages. In addition, Gra treatment increased the intracellular reactive oxygen species (ROS) levels of C. elegans and M. incognita. Molecular docking interaction analysis indicated that Gra could bind and interact with GCS-1, GST-4, and DAF-16a in order of low binding energy, followed by SOD-3, SKN-1, and DAF-16b. This implies that the anthelmintic action of Gra is related to the oxidative stress response. To validate this mechanism, we examined the expression of the genes involved in the oxidative stress responses following treatment with Gra using transgenic C. elegans strains such as the TJ356 strain zIs356 [daf-16p::daf-16a/b::GFP + rol-6 (su1006)], LD1 ldIs7 [skn-1p::skn-1b/c::GFP + rol-6 (su1006)], LD1171 ldIs3 [gcs-1p::GFP + rol-6 (su1006)], CL2166 dvIs19 [(pAF15) gst-4p::GFP::NLS], and CF1553 strain muIs84 [(pAD76) sod-3p::GFP + rol-6 (su1006)]. Gra treatment caused nuclear translocation of DAF-16/FoxO and enhanced gst-4::GFP expression, but it had no change in sod-3::GFP expression. These results indicate that Gra induces oxidative stress response via phase II detoxification without reduced cellular redox machinery. Gra treatment also inhibited the nuclear localization of SKN-1::GFP in the intestine, which may lead to a condition in which oxidative stress tolerance is insufficient to protect C. elegans by the inactivation of SKN-1, thus inducing nematode lethality. Furthermore, Gra caused the mortality of two mutant strains of C. elegans, CB113 and DA1316, which are resistant to aldicarb and ivermectin, respectively. This indicates that the mode of action of Gra is different from the traditional nematicides currently in use, suggesting that it could help develop novel approaches to control plant-parasitic nematodes.

Structure-Guided Design of G-Protein-Coupled Receptor Polypharmacology.

Many diseases are polygenic and can only be treated efficiently with drugs that modulate multiple targets. However, rational design of compounds with multi-target profiles is rarely pursued because it is considered too difficult, in particular if the drug must enter the central nervous system. Here, a structure-based strategy to identify dual-target ligands of G-protein-coupled receptors is presented. We use this approach to design compounds that both antagonize the A2A adenosine receptor and activate the D2 dopamine receptor, which have excellent potential as antiparkinson drugs. Atomic resolution models of the receptors guided generation of a chemical library with compounds designed to occupy orthosteric and secondary binding pockets in both targets. Structure-based virtual screens identified ten compounds, of which three had affinity for both targets. One of these scaffolds was optimized to nanomolar dual-target activity and showed the predicted pharmacodynamic effect in a rat model of Parkinsonism.

Information Theory and an Entropic Approach to an Analysis of Fiscal Inequality.

In his influential study, Theil (1967) developed the notion of entropy on the basis of information theory. He then advocated the use of entropy-based measure for the analysis of income inequality. In this paper, the first of its kind, we apply Theil's notion of entropy to public finances in multi-tiered governments, in particular for a measurement of fiscal decentralisation, which is currently very crude in terms of the ratio between local government revenue and total revenue. It is the claim of this paper that such an approach of measuring fiscal decentralisation completely ignores important distributional aspects of fiscal arrangements. Findings from this paper indicate that studies on measuring various aspects of fiscal activities-such as fiscal decentralisation-should carefully take into account the dispersion of revenue (and expenditure) across regions. On that basis, the entropic approach developed in this paper is able to accommodate these dispersions across subnational governments. As an illustration for the case of Vietnam, the true degree of fiscal decentralization has effectively been decreased in comparison with estimates from other simple measurements due to the presence of substantial dispersions of revenue and expenditure from the subnational governments across 63 provinces in Vietnam.

Building of neomycin-nucleobase-amino acid conjugates for the inhibition of oncogenic miRNAs biogenesis.

MicroRNAs (miRNAs) are a recently discovered category of small RNA molecules that regulate gene expression at the post-transcriptional level. Accumulating evidence indicates that miRNAs are aberrantly expressed in a variety of human cancers, thus being oncogenic. The inhibition of oncogenic miRNAs (defined as the blocking of miRNAs' production or function) would find application in the therapy of different types of cancer in which these miRNAs are implicated. In this work, we describe the design and synthesis of new small-molecule RNA ligands with the aim of inhibiting Dicer-mediated processing of oncogenic miRNAs. One of the synthesized compound (4b) composed of the aminoglycoside neomycin conjugated to an artificial nucleobase and to amino acid histidine is able to selectively decrease miR-372 levels in gastric adenocarcinoma (AGS) cells and to restore the expression of the target LATS2 protein. This activity led to the inhibition of proliferation of these cells. The study of the interactions of 4b with pre-miR-372 allowed for the elucidation of the molecular mechanism of the conjugate, thus leading to new perspectives for the design of future inhibitors.

Oncogenic MicroRNAs Biogenesis as a Drug Target: Structure-Activity Relationship Studies on New Aminoglycoside Conjugates.

MicroRNAs (miRNAs) are a recently discovered category of small RNA molecules that regulate gene expression at the post-transcriptional level. Accumulating evidence indicates that miRNAs are aberrantly expressed in a variety of human cancers and that the inhibition of these oncogenic miRNAs could find application in the therapy of different types of cancer. Herein, we describe the synthesis and biological evaluation of new small-molecule drugs that target oncogenic miRNAs production. In particular, we chose to target two miRNAs (i.e., miRNA-372 and -373) implicated in various types of cancer, such as gastric cancer. Their precursors (pre-miRNAs) are overexpressed in cancer cells and lead to mature miRNAs after cleavage of their stem-loop structure by the enzyme Dicer in the cytoplasm. Some of the newly synthesized conjugates can inhibit Dicer processing of the targeted pre-miRNAs in vitro with increased efficacy relative to our previous results (D.D. Vo et al., ACS Chem. Biol. 2014, 9, 711-721) and, more importantly, to inhibit proliferations of adenocarcinoma gastric cancer (AGS) cells overexpressing these miRNAs, thus representing promising leads for future drug development.

Total Synthesis of Viniferifuran, Resveratrol-Piceatannol Hybrid, Anigopreissin A and Analogues - Investigation of Demethylation Strategies.

Resveratrol-based natural products constitute a valuable source of unique compounds with diverse biological activities. In this report we investigate demethylation strategies to minimize formation of cyclized and dimerized products during the synthesis of viniferifuran and analogues. We found that boron trichloride/tetra-n-butylammonium iodide (BCl3/TBAI) is typically more effective than boron tribromide (BBr3). Based on these findings we carried out the first syntheses of dehydro-δ-viniferin, resveratrol-piceatannol hybrid and anigopreissin A. In addition, we have developed a short and efficient route to viniferifuran that was obtained in 13% yield over six steps.

Ribosome-targeting antibiotics as inhibitors of oncogenic microRNAs biogenesis: Old scaffolds for new perspectives in RNA targeting.

MicroRNAs (miRNAs) are non-coding RNAs that regulate gene expression at the post-transcriptional level. It is now well established that the overexpression of some miRNAs (oncogenic miRNAs) is responsible for initiation and progression of human cancers and the discovery of new molecules able to interfere with their production and/or function represents one of the most important challenges of current medicinal chemistry of RNA ligands. In this work, we studied the ability of 18 different antibiotics, known as prokaryotic ribosomal RNA, to bind to oncogenic miRNA precursors (stem-loop structured pre-miRNAs) in order to inhibit miRNAs production. In vitro inhibition, binding constants, thermodynamic parameters and binding sites were investigated and highlighted that aminoglycosides and tetracyclines represent interesting pre-miRNA ligands with the ability to inhibit Dicer processing.

A combination of in silico and SAR studies to identify binding hot spots of Bcl-xL inhibitors.

Inhibition of Bcl-2 family protein-protein interactions (PPI) is a very promising direction in cancer chemotherapy. Hence over the last decade, many medicinal chemistry studies endeavoured to discover drug candidates, and a wealth of chemical scaffolds with striking chemical diversity was reported as Bcl-xL inhibitors. This raises the question of whether all these molecules could occupy a unique binding site, or rather discrete pockets of the protein surface. To test if small and chemically diverse Bcl-xL inhibitors are likely to bind a single pocket, and to identify which pocket, we used a battery of computational and modeling approaches. We first checked that the large dataset of Bcl-xL inhibitors we built can actually fit to a universal pharmacophore. Then we defined the probable binding hot spots of interaction through comparison of crystal structures, as well as virtual fragment screening. Finally, new analogues of small polyphenol derivatives were synthesized to precisely probe a hydrogen bond suggested by docking experiments. Bcl-xL inhibition potency of these products confirmed the predicted binding mode. This combination of X-ray structure exploration, molecular modeling studies and medicinal chemistry supports that all these small Bcl-xL inhibitors occupy the same hot spot of interaction. The identification of this binding site should help the design and optimization of small PPI Bcl-xL inhibitors.

Design, synthesis and biological evaluation of new inhibitors of Bax/Bcl-xL interaction in cancer cells.

We describe the synthesis of a series of new molecules containing phenol and triazoles moieties, compounds which have been evaluated for their ability to inhibit Bax/Bcl-xL interactions in cancer cells, by using BRET assays, and to induce cell death. Several derivatives exhibit a very promising activity, being more potent than the reference compounds acylpyrogallol A and ABT-737. These preliminary results demonstrate that derivatives of this family can be attractive to develop new molecules with potent anticancer activity.

Does institutional quality matter for financial inclusion? International evidence.

Financial inclusion is pivotal in supporting sustainable economic growth and social transformation. It is a key enabler for reducing poverty and uplifting prosperity. Improving financial inclusion has attracted significant attention from practitioners, academics, and governments. However, the asymmetric effect of institutional quality on financial inclusion contingent upon the income level has largely been neglected in the existing literature. As such, this study examines this asymmetric effect using the panel smooth transition regression for a sample of 110 countries globally from 2004 to 2020. Our empirical findings confirm the asymmetric effect of institutional quality on financial inclusion depending on the income level. Improved institutional quality is associated with extended financial inclusion in high-income and middle-income countries. However, low-income countries may not benefit from their institutional reform. Policy implications have emerged based on these empirical findings.

Drivers of domestic migration in Vietnam: The characteristics of the households and their heads, environmental factors and living conditions.

Vietnam has achieved significant economic growth, poverty reduction, and social transformation since its 1986 major economic reform. However, industrialization, a key pillar supporting this achievement, has resulted in massive domestic migration from certain parts of the country into industrialized provinces mainly located in the south of Vietnam, leading to various challenges for society. This study investigates the effects of the characteristics of Vietnamese households and their heads, environmental factors, and living conditions of the households in the regions where they have decided to leave behind for a migration decision on domestic migration. Our study also compares the migration trends in the past decade using the Vietnamese Household Living Standard Surveys (VHLSS) in 2010 and 2020, together with a logit model. We find that the average probability that a household and their members migrate is about 10 per cent in 2010, reduced to approximately 6.8 per cent in 2020. Our empirical findings also confirm that a migration decision is strongly associated with the characteristics of the households and their heads, particularly for the household size and the educational level of the household head. The average radiation and rainfall are also associated with a migration decision. Weather temperature, water sources, and electricity supply also play an essential role in Vietnamese households' migration decisions. Policy implications have emerged based on these empirical findings that the Vietnamese government should consider.

Understanding the characteristics of the household energy transition in a developing country.

Understanding the energy transition process in developing countries is crucial to implement policies to reduce the use of traditional fossil fuel-based energy sources, which increase pollution, worsen global climate change, and negatively impact people's health. Existing literature indicates that households account for approximately 25% of total energy consumption for consumption and production activities. However, understanding the energy consumption patterns of choices of energy sources and their determinants has largely been neglected in the existing literature. As such, this study uses the multivariate probit model to identify the factors influencing household energy choices in Vietnam, using data from 2016 to 2020 from the Vietnamese Households Living Standard Surveys (VHLSS). Our study focuses on how households' multiple occupations, particularly in rural areas, affect energy sources choices. We find that households participate in different agricultural sub-sectors simultaneously, resulting in differential access to multiple energy sources. Households engaging in cultivation, forestry, and animal husbandry activities are more likely to choose coal, fuelwood, and biomass as the primary energy sources for production and daily uses. In contrast, higher household income and household head with higher education level also increases the likelihood of choosing cleaner energy choices for daily uses and production activities. In addition, our empirical findings confirm the validity of the "energy stacking" hypothesis rather than the "energy ladders" hypothesis - two contrasting hypotheses concerning household energy transition in the literature. Policy implications have emerged based on the findings of this paper to enhance the clean energy transition in Vietnam in achieving sustainable economic development and social transformation and her commitment to combating global climate change issues.