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Objectives: To describe the clinical, paraclinical characteristics and the short-term results of laparoscopic distal gastrectomy with intracorporeal anastomosis for the treatment of stomach cancer. Subjects and methods: A descriptive and retrospective study on 109 patients undergoing laparoscopic distal gastrectomy with intracorporeal anastomosis at Vietnam National Cancer Hospital between January 2019 and July 2022. Results: Patients were mostly men, > 50 years old. Duration of symptom onset to hospital admission ≤ 3 months and epigastric abdominal pain were the most common symptoms. The average surgery duration was 202 minutes, 90.8% of the patients had Billroth I anastomosis (Delta shaped). Post-operative outcomes recorded very few complications, with a fast recovery time. Conclusion: Laparoscopic distal gastrectomy with intracorporeal anastomosis is a minimally invasive surgical method with a safe early result and fast post-operative recovery time.

As authorities braced for the arrival of the Omicron variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), infrastructure investments and government directives prompted action in central Viet Nam to establish capacity for genomic surveillance sequencing. From 17 November 2021 to 7 January 2022, the Pasteur Institute in Nha Trang sequenced 162 specimens from 98 150 confirmed SARS-CoV-2 cases in the region collected from 8 November to 31 December 2021. Of these, all 127 domestic cases were identified as the B.1.617.2 (Delta) variant, whereas 92% (32/35) of imported cases were identified as the B.1.1.529 (Omicron) variant, all among international flight passengers. Patients were successfully isolated, enabling health-care workers to prepare for additional cases. Most (78%) of the 32 Omicron cases were fully vaccinated, suggesting continued importance of public health and social measures to control the spread of new variants.

We show that lenders charge higher interest rates for mortgages on properties exposed to a greater risk of sea level rise (SLR). This SLR premium is not evident in short-term loans and is not related to borrowers’ short-term realized default or creditworthiness. Further, the SLR premium is smaller when the consequences of climate change are less salient and in areas with more climate change deniers. Overall, our results suggest that mortgage lenders view the risk of SLR as a long-term risk and that attention and beliefs are potential barriers through which SLR risk is priced in residential mortgage markets.

We document novel evidence on the spillover effect of a corporate control regulation on local mortgage markets. We find that banks directly targeted by the Sarbanes-Oxley Act (SOX) to rectify their internal control weaknesses reduce mortgage originations following the regulation’s enactment. This causes mortgage credit to be reallocated toward other banks in the same local markets: while competing public banks expand lending to safer borrowers, private banks increase lending toward risky applicants. Consequently, loans originated by private banks in spillover counties report higher default rates. (JEL E51, G21, G38) Received February 27, 2021; editorial decision August 21, 2022 by Editor Camelia Kuhnen. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

Molecular surface representations have been advertised as a great tool to study protein structure and functions, including protein-ligand binding affinity modeling. However, the conventional surface-area-based methods fail to deliver a competitive performance on the energy scoring tasks. The main reason is the lack of crucial physical and chemical interactions encoded in the molecular surface generations. We present novel molecular surface representations embedded in different scales of the element interactive manifolds featuring the dramatically dimensional reduction and accurately physical and biological properties encoders. Those low-dimensional surface-based descriptors are ready to be paired with any advanced machine learning algorithms to explore the essential structure-activity relationships that give rise to the element interactive surface area-based scoring functions (EISA-score). The newly developed EISA-score has outperformed many state-of-the-art models, including various well-established surface-related representations, in standard PDBbind benchmarks.

Currently, there is neither effective antiviral drugs nor vaccine for coronavirus disease 2019 (COVID-19) caused by acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Due to its high conservativeness and low similarity with human genes, SARS-CoV-2 main protease (Mpro) is one of the most favorable drug targets. However, the current understanding of the molecular mechanism of Mpro inhibition is limited by the lack of reliable binding affinity ranking and prediction of existing structures of Mpro–inhibitor complexes. This work integrates mathematics (i.e., algebraic topology) and deep learning (MathDL) to provide a reliable ranking of the binding affinities of 137 SARS-CoV-2 Mpro inhibitor structures. We reveal that Gly143 residue in Mpro is the most attractive site to form hydrogen bonds, followed by Glu166, Cys145, and His163. We also identify 71 targeted covalent bonding inhibitors. MathDL was validated on the PDBbind v2016 core set benchmark and a carefully curated SARS-CoV-2 inhibitor dataset to ensure the reliability of the present binding affinity prediction. The present binding affinity ranking, interaction analysis, and fragment decomposition offer a foundation for future drug discovery efforts., By integrating algebraic topology and deep learning, we provide a reliable ranking of binding affinities, binding site analysis, and fragment decomposition for 137 SARS-CoV-2 main protease inhibitors.