KoNA: Korean Nucleotide Archive as A New Data Repository for Nucleotide Sequence Data.

During the last decade, the generation and accumulation of petabase-scale high-throughput sequencing data have resulted in great challenges, including access to human data, as well as transfer, storage, and sharing of enormous amounts of data. To promote data-driven biological research, the Korean government announced that all biological data generated from government-funded research projects should be deposited at the Korea BioData Station (K-BDS), which consists of multiple databases for individual data types. Here, we introduce the Korean Nucleotide Archive (KoNA), a repository of nucleotide sequence data. As of July 2022, the Korean Read Archive in KoNA has collected over 477 TB of raw next-generation sequencing data from national genome projects. To ensure data quality and prepare for international alignment, a standard operating procedure was adopted, which is similar to that of the International Nucleotide Sequence Database Collaboration. The standard operating procedure includes quality control processes for submitted data and metadata using an automated pipeline, followed by manual examination. To ensure fast and stable data transfer, a high-speed transmission system called GBox is used in KoNA. Furthermore, the data uploaded to or downloaded from KoNA through GBox can be readily processed using a cloud computing service called Bio-Express. This seamless coupling of KoNA, GBox, and Bio-Express enhances the data experience, including submission, access, and analysis of raw nucleotide sequences. KoNA not only satisfies the unmet needs for a national sequence repository in Korea but also provides datasets to researchers globally and contributes to advances in genomics. The KoNA is available at https://www.kobic.re.kr/kona/.

Accomplishing High-Performance Organic Solar Sub-Modules (≈55 cm2) with >16% Efficiency by Controlling the Aggregation of an Engineered Non-Fullerene Acceptor.

The fabrication of environmentally benign, solvent-processed, efficient, organic photovoltaic sub-modules remains challenging due to the rapid aggregation of the current high performance non-fullerene acceptors (NFAs). In this regard, design of new NFAs capable of achieving optimal aggregation in large-area organic photovoltaic modules has not been realized. Here, an NFA named BTA-HD-Rh is synthesized with longer (hexyl-decyl) side chains that exhibit good solubility and optimal aggregation. Interestingly, integrating a minute amount of new NFA (BTA-HD-Rh) into the PM6:L8-BO system enables the improved solubility in halogen-free solvents (o-xylene:carbon disulfide (O-XY:CS2)) with controlled aggregation is found. Then solar sub-modules are fabricated at ambient condition (temperature at 25 ± 3 °C and humidity: 30-45%). Ultimately, the champion 55 cm2 sub-modules achieve exciting efficiency of >16% in O-XY:CS2 solvents, which is the highest PCE reported for sub-modules. Notably, the highest efficiency of BTA-HD-Rh doped PM6:L8-BO is very well correlated with high miscibility with low Flory-Huggins parameter (0.372), well-defined nanoscale morphology, and high charge transport. This study demonstrates that a careful choice of side chain engineering for an NFA offers fascinating features that control the overall aggregation of active layer, which results in superior sub-module performance with environmental-friendly solvents.

π-Conjugated Polymer with Pendant Side Chains as a Dopant-Free Hole Transport Material for High-Performance Perovskite Solar Cells.

Dopant-free polymeric hole transport materials (HTMs) have attracted considerable attention in perovskite solar cells (PSCs) due to their high carrier mobilities and excellent hydrophobicity. They are considered promising candidates for HTMs to replace commercial Spiro-OMeTAD to achieve long-term stability and high efficiency in PSCs. In this study, we developed BDT-TA-BTASi, a conjugated donor-π-acceptor polymeric HTM. The donor benzo[1,2-b:4,5-b']dithiophene (BDT) and acceptor benzotriazole (BTA) incorporated pendant siloxane, and alkyl side chains led to high hole mobility and solubility. In addition, BDT-TA-BTASi can effectively passivate the perovskite layer and markedly decrease the trap density. Based on these advantages, dopant-free BDT-TA-BTASi-based PSCs achieved an efficiency of over 21.5%. Furthermore, dopant-free BDT-TA-BTASi-based devices not only exhibited good stability in N2 (retaining 92% of the initial efficiency after 1000 h) but also showed good stability at high-temperature (60 °C) and -humidity conditions (80 ± 10%) (retaining 92 and 82% of the initial efficiency after 400 h). These results demonstrate that BDT-TA-BTASi is a promising HTM, and the study provides guidance on dopant-free polymeric HTMs to achieve high-performance PSCs.

Pontocerebellar Hypoplasia 7 with Novel Compound Heterozygous Variants of TOE1 in a Boy with Micropenis, Developmental Delay, and Ataxia: The First Korean Case Report.

Pontocerebellar hypoplasia (PCH) is a rare neurodegenerative disorder characterized by hypoplasia of the pons and cerebellum and global developmental delay. Among several PCH types, PCH7 is a characteristic type that manifests with not only brain lesions but also sexual developmental disorders. The causative gene, TOE1, encodes a protein involved in small ribonucleic acid maturation and processing. TOE1 mutation is associated with neuronal survival that causes hypoplasia of the cerebellum and pons. We report the case of a male patient with PCH7, developmental delay, ataxia, micropenis, and undescended testis. Genetic analysis revealed compound heterozygous missense variants (c.955C>T and c.533T>G) in the TOE1 gene.

FSP1 confers ferroptosis resistance in KEAP1 mutant non-small cell lung carcinoma in NRF2-dependent and -independent manner.

Ferroptosis, a type of cell death induced by lipid peroxidation, has emerged as a novel anti-cancer strategy. Cancer cells frequently acquire resistance to ferroptosis. However, the underlying mechanisms are poorly understood. To address this issue, we conducted a thorough investigation of the genomic and transcriptomic data derived from hundreds of human cancer cell lines and primary tissue samples, with a particular focus on non-small cell lung carcinoma (NSCLC). It was observed that mutations in Kelch-like ECH-associated protein 1 (KEAP1) and subsequent nuclear factor erythroid 2-related factor 2 (NRF2, also known as NFE2L2) activation are strongly associated with ferroptosis resistance in NSCLC. Additionally, AIFM2 gene, which encodes ferroptosis suppressor protein 1 (FSP1), was identified as the gene most significantly correlated with ferroptosis resistance, followed by multiple NRF2 targets. We found that inhibition of NRF2 alone was not sufficient to reduce FSP1 protein levels and promote ferroptosis, whereas FSP1 inhibition effectively sensitized KEAP1-mutant NSCLC cells to ferroptosis. Furthermore, we found that combined inhibition of FSP1 and NRF2 induced ferroptosis more intensely. Our findings imply that FSP1 is a crucial suppressor of ferroptosis whose expression is partially dependent on NRF2 and that synergistically targeting both FSP1 and NRF2 may be a promising strategy for overcoming ferroptosis resistance in cancer.

The Prognostic Significance of Leukocyte Count on All-Cause and Cardiovascular Disease Mortality: A Systematic Review and Meta-Analysis.

White blood cells (WBCs) act as mediators of inflammatory responses and are commonly measured in hospitals. Although several studies have reported a relation between WBC count and mortality, no systematic review or meta-analysis has been conducted. This study aimed to identify an association between WBC count and mortality. We conducted a systematic search on Embase using keywords such as "white blood cell" and "mortality." We analyzed the hazard ratios (HRs) for WBC count of 1.0 × 109 cells/L regarding 2 criteria: the cause of mortality and the follow-up period. A total of 13 of 222 articles comprising a total of 62,904 participants were included in this study, meeting the criteria set. A positive association was observed between WBC count and mortality, as indicated by an HR of 1.10 (95% confidence interval [CI] 1.08 to 1.13). In additionally, WBC count emerged as a significant predictor of mortality in both groups, with an HR of 1.10 (95% CI 1.07 to 1.12) for patients with cardiovascular disease and an HR of 1.12 (95% CI 1.07 to 1.17) for the general population or patients with COVID-19. Furthermore, a higher WBC count demonstrated a significant association with long-term all-cause mortality (HR 1.09, 95% CI 1.07 to 1.12) and long-term cardiovascular mortality (HR 1.05, 95% CI 1.02 to 1.07). Similarly, a significant association was found between higher WBC count and short-term all-cause mortality (HR 1.12, 95% CI 1.09 to 1.16) and cardiovascular mortality (HR 1.12, 95% CI 1.07 to 1.17). Further research is necessary to explore the relation between WBC count and disease progression or death and to establish causality between elevated WBC count and disease progression.

Multifunctional Narrow Band Gap Terpolymer-Enabled High-Performance Dopant-Free Perovskite and Additive-Free Organic Solar Cells with Long-Term Stability.

The optoelectronic devices endowing multifunctionality while utilizing a single low-cost material have always been challenging. For this purpose, we adopted a random ternary copolymerization strategy for designing two terpolymers, namely TP-0.8-EG and TP-0.8-TEG comprising a benzothiadiazole (BT)-benzo[1,2-b:4,5-b']dithiophene-diketopyrrolo[3,4-c]pyrrole (A1-π-D-π-A2) backbone. The figure of merits of the narrow band gap TP-0.8-EG terpolymer include deepened frontier energy levels, high hole mobility, better film formability, enriched multifunctionality, and passivation capability. Accordingly, the suitable electronic properties of TP-0.8-EG revealed that it can function as a dopant-free hole-transporting material in perovskite solar cells (PSCs) as well as the third component in organic solar cells (OSCs). Remarkably, TP-0.8-EG outperforms by exhibiting a higher power conversion efficiency (PCE) of 20.9% over TP-0.8-TEG (PCE of 18.3%) and BT-UF (PCE of 14.6%) in dopant-free PSCs. Interestingly, TP-0.8-EG fabricated along with PM6:Y7 displayed a high PCE of 16.52% in ternary OSCs. Also, TP-0.8-EG established good device storage stabilities (85 and 83% of their initial PCEs for 1200 and 500 h) in dopant-free PSC as well as OSC devices. Notably, the devices with TP-0.8-EG showed excellent thermal and moisture stabilities. To the best of our knowledge, A1-π-D-π-A2 terpolymer performing both in PSCs and OSCs with decent efficiencies and good device stabilities is a rare scenario.

Introduction of the Korea BioData Station (K-BDS) for sharing biological data.

A wave of new technologies has created opportunities for the cost-effective generation of high-throughput profiles of biological systems, foreshadowing a "data-driven science" era. The large variety of data available from biological research is also a rich resource that can be used for innovative endeavors. However, we are facing considerable challenges in big data deposition, integration, and translation due to the complexity of biological data and its production at unprecedented exponential rates. To address these problems, in 2020, the Korean government officially announced a national strategy to collect and manage the biological data produced through national R&D fund allocations and provide the collected data to researchers. To this end, the Korea Bioinformation Center (KOBIC) developed a new biological data repository, the Korea BioData Station (K-BDS), for sharing data from individual researchers and research programs to create a data-driven biological study environment. The K-BDS is dedicated to providing free open access to a suite of featured data resources in support of worldwide activities in both academia and industry.

Finely Tuned Molecular Packing Realized by a New Rhodanine-Based Acceptor Enabling Excellent Additive-Free Small- and Large-Area Organic Photovoltaic Devices Approaching 19 and 12.20% Efficiencies.

A new nonfullerene acceptor (NFA), BTA-ERh, was synthesized and integrated into a PM6:Y7:PC71BM ternary system to regulate the blend film morphology for enhanced device performance. Due to BTA-ERh's good miscibility with host active blend films, an optimized film morphology was obtained with appropriate phase separation and fine-tuning of film crystallinity, which ultimately resulted in efficient exciton dissociation, charge transport, lower recombination loss, and decreased trap-state density. The resulting additive-free quaternary devices achieved a remarkable efficiency of 18.90%, with a high voltage, fill factor, and current density of 0.87 V, 76.32%, and 28.60 mA cm-2, respectively. By adding less of a new small molecule with high crystallinity, the favorable nanomorphology shape of blend films containing NFAs might be adjusted. Consequently, this strategy can enhance photovoltaic device performance for cutting-edge NFA-based organic solar cells (OSCs). In contrast, the additive-free OSCs exhibited good operational stability. More importantly, large-area modules with the quaternary device showed a remarkable efficiency of 12.20%, with an area as high as 55 cm2 (substrate size, 100 cm2) in an air atmosphere via D-bar coating. These results highlight the enormous research potential for a multicomponent strategy for future additive-free OSC applications.

Changes in visits to green spaces due to the COVID-19 pandemic: Focusing on the proportion of repeat visitors and the distances between green spaces and visitors' places of residences.

Through a quantitative approach, this study aimed to clarify the changes in the number of visitors and visits to green spaces according to green space type before and after the COVID-19 pandemic. We explored the changes in the proportion of repeat visitors and the distance between green spaces and visitors' places of residence. We used KDDI Location Analyzer, which performs novel analysis using mobile phone GPS and census data. The study area included 10 target sites (urban parks and nature trails in the backcountry) located in the Sapporo metropolitan area in Japan. The survey period included snow-free seasons from 2019 to 2021, and 2019 was considered the period "before the pandemic." The results revealed that the number of visits during the pandemic increased compared with those before the pandemic, except for those of urban parks near the city center. In 2020, the proportion of repeat visitors increased for all 10 target sites. In addition, since the outbreak of the pandemic, distances between all urban parks and visitors' residences decreased. The same trend was observed for nature trails in the backcountry close to the city center. These findings indicate a generally decreasing trend in the number of visits to green spaces as many people have been refraining from visiting the site since the outbreak of the pandemic. Contrastingly, the number of visits by repeat visitors who reside close to the target sites has increased in some cases, which compensated for the general decreases.

Investigation of early molecular alterations in tauopathy with generative adversarial networks.

The recent advances in deep learning-based approaches hold great promise for unravelling biological mechanisms, discovering biomarkers, and predicting gene function. Here, we deployed a deep generative model for simulating the molecular progression of tauopathy and dissecting its early features. We applied generative adversarial networks (GANs) for bulk RNA-seq analysis in a mouse model of tauopathy (TPR50-P301S). The union set of differentially expressed genes from four comparisons (two phenotypes with two time points) was used as input training data. We devised four-way transition curves for a virtual simulation of disease progression, clustered and grouped the curves by patterns, and identified eight distinct pattern groups showing different biological features from Gene Ontology enrichment analyses. Genes that were upregulated in early tauopathy were associated with vasculature development, and these changes preceded immune responses. We confirmed significant disease-associated differences in the public human data for the genes of the different pattern groups. Validation with weighted gene co-expression network analysis suggested that our GAN-based approach can be used to detect distinct patterns of early molecular changes during disease progression, which may be extremely difficult in in vivo experiments. The generative model is a valid systematic approach for exploring the sequential cascades of mechanisms and targeting early molecular events related to dementia.

VPrimer: A Method of Designing and Updating Primer and Probe With High Variant Coverage for RNA Virus Detection.

Fatal infectious diseases caused by RNA viruses, such as COVID-19, have emerged around the world. RT-PCR is widely employed for virus detection, and its accuracy depends on the primers and probes since RT-PCR can detect a virus only when the primers and probes bind to the target gene of the virus. Most of primer design methods are for a single host and so require a great deal of effort to design for RNA virus detection, including homology tests among the host and all the viruses for the host using BLAST-like tools. Furthermore, they do not consider variant sequences, which are very common in viruses. In this study, we describe VPrimer, a method of designing high-quality primer-probe sets for RNA viruses. VPrimer can find primer-probe sets that cover more than 95% of the variants of a target virus but do not cover any sequences of other viruses or the host. With VPrimer, we found 381,698,582 primer-probe sets for 3,104 RNA viruses. Multiplex PCR assays using the top 2 primer-probe sets suggested by VPrimer usually cover 100% of variants. To address the rapid changes in viral genomes, VPrimer finds the best and up-to-date primer-probe sets incrementally against the most recently reported variants.

DSCR1 deficiency ameliorates the Aß pathology of Alzheimer's disease by enhancing microglial activity.

Microglial phagocytosis and clearance are important for the removal of amyloid-ß (Aß) plaques in Alzheimer's disease (AD). Chronic exposure of microglia to Aß plaques leads to microglial metabolic dysfunction, and dysregulation of microglia can accelerate the deposition of Aß plaques and cause learning and memory impairment. Thus, regulating microglial Aß clearance is crucial for the development of therapeutics for AD-related dementia. Here, Down syndrome critical region 1 (DSCR1) deficiency ameliorated Aß plaque deposition in the 5xFAD mouse model of AD by altering microglial activity; however, the Aß synthesis pathway was not affected. DSCR1 deficiency improved spatial learning and memory impairment in 5xFAD mice. Furthermore, DSCR1-deficient microglia exhibited accelerated lysosomal degradation of Aß after phagocytosis, and BV2 cells with stable knockdown of DSCR1 demonstrated enhanced lysosomal activity. RNA-sequencing analysis showed that the transcriptional signatures associated with responses to IFN-γ were significantly up-regulated in DSCR1-knockdown BV2 cells treated with Aß. Our data strongly suggest that DSCR1 is a critical mediator of microglial degradation of amyloid plaques and a new potential microglial therapeutic target in AD.

Precise single-cell transcriptomic mapping of normal and leukemic cell states reveals unconventional lineage priming in acute myeloid leukemia.

Initial classification of acute leukemia involves the assignment of blasts to cell states within the hematopoietic hierarchy based on morphological and immunophenotypic features. Yet, these traditional classification approaches lack precision, especially at the level of immature blasts. Single-cell RNA-sequencing (scRNA-seq) enables precise determination of cell state using thousands of markers, thus providing an opportunity to re-examine present-day classification schemes of acute leukemia. Here, we developed a detailed reference map of human bone marrow hematopoiesis from 263,519 single-cell transcriptomes spanning 55 cellular states. Cell state annotations were benchmarked against purified cell populations, and in-depth characterization of gene expression programs underlying hematopoietic differentiation was undertaken. Projection of single-cell transcriptomes from 175 samples spanning acute myeloid leukemia (AML), mixed phenotype acute leukemia (MPAL), and acute erythroid leukemia (AEL) revealed 11 subtypes involving distinct stages of hematopoietic differentiation. These included AML subtypes with notable lymphoid or erythroid lineage priming, challenging traditional diagnostic boundaries between AML, MPAL, and AEL. Quantification of lineage priming in bulk patient cohorts revealed specific genetic alterations associated with this unconventional lineage priming. Integration of transcriptional and genetic information at the single-cell level revealed how genetic subclones can induce lineage restriction, differentiation blocks, or expansion of mature myeloid cells. Furthermore, we demonstrate that distinct cellular hierarchies can co-exist within individual patients, providing insight into AML evolution in response to varying selection pressures. Together, precise mapping of hematopoietic cell states can serve as a foundation for refining disease classification in acute leukemia and understanding response or resistance to emerging therapies.

Differentiation of industrial hemp strains by their cannabinoid and phenolic compounds using LC × LC-HRMS.

Cannabis is an ancient plant that has been used for therapeutic and recreational purposes. Nowadays, industrial hemp, a variety with low concentration of the psychoactive cannabinoid Δ9-tetrahydrocannabinol (THC) and high concentration of non-psychoactive cannabinoids, is getting more and more interest in the food, pharmaceutical, and cosmetic industry. However, cannabis not only contains cannabinoids as bioactive components but also other metabolites like terpenes and phenolic compounds, and the content of these interesting secondary metabolites greatly differs with the genetic variety of the plant. Due to the huge complexity of composition of the cannabis matrix, in this work, a comprehensive two-dimensional liquid chromatography (LC × LC) method has been developed as a very power separation technique coupling a pentafluorophenyl (PFP) and a C18 in the first and second dimensions. Two industrial hemp strains (cookie and gelato) were analyzed to determine the difference in their content of cannabinoids and phenolic compounds. To do this, a new demodulation process was applied for the first time to transform 2D raw data into 1D data which allowed carrying out the chemometric analysis needed to determine the statistical differences between the hemp strains. The cookie strain presented a total of 41 cannabinoid markers, while the gelato strain presented more representative phenolic compounds, in total 24 phenolic compounds were detected as potential markers of this sample. These differences in the chemical composition could determine the industrial destiny of the different hemp strains.

Impact of Aryl End Group Engineering of Donor Polymers on the Morphology and Efficiency of Halogen-Free Solvent-Processed Nonfullerene Organic Solar Cells.

End group engineering on the side chain of π-conjugated donor polymers is explored as an effective way to develop efficient photovoltaic devices. In this work, we designed and synthesized three new π-conjugated polymers (PBDT-BZ-1, PBDT-S-BZ, and PBDT-BZ-F) with terminal aryl end groups on the side chain of chlorine-substituted benzo[1,2-b:4,5b']dithiophene (BDT). End group modifications showed notable changes in energy levels, dipole moments, exciton lifetimes, energy losses, and charge transport properties. Remarkably, the three new polymers paired with IT-4F (halogen-free solvent processed/toluene:DPE) displayed high power conversion efficiencies (PCEs) compared to a polymer (PBDT-Al-5) without a terminal end group (PCE of 7.32%). Interestingly, PBDT-S-BZ:IT-4F (PCE of 13.73%) showed a higher PCE than the benchmark PM7:IT-4F. The improved performance of PBDT-S-BZ well correlates with its improved charge mobility, well-interdigitated surface morphology, and high miscibility with a low Flory-Huggins interaction parameter (1.253). Thus, we successfully established a correlation between the end group engineering and bulk properties of the new polymers for realizing the high performance of halogen-free nonfullerene organic solar cells.

Effect of postoperative non-steroidal anti-inflammatory drugs on anastomotic leakage after pancreaticoduodenectomy.

BACKGROUND: Although the association between an increase in anastomotic leakage (AL) and non-steroidal anti-inflammatory drugs (NSAIDs) has been reported in gastrointestinal surgeries, this issue has rarely been addressed for pancreaticoduodenectomy (PD). We aimed to investigate the association between postoperative NSAIDs administration and clinically relevant AL (CR-AL) following PD. METHODS: We retrospectively evaluated 2,163 consecutive patients who underwent PD between 2007 and 2019. The patients were divided into two groups; patients who received and did not receive NSAIDs by postoperative day (POD) 5. We conducted a propensity score analysis using inverse probability of treatment weighting (IPTW) to adjust the baseline differences between both groups. We compared the occurrence of CR-AL and other postoperative outcomes before and after IPTW. Further, we used the multivariable binary logistic regression method for a sensitivity analysis for CR-AL. RESULTS: A total of 2,136 patients were included in the analysis. Of these, 222 (10.4%) received NSAIDs by POD 5. The overall occurrence rate of CR-AL was 14.9%. After IPTW, postoperative NSAIDs were significantly associated with CR-AL (odds ratio [OR]: 1.24, 95% CI [1.05, 1.47], P = 0.012), prolonged postoperative hospitalization (OR: 1.31, 95% CI [1.14, 1.50], P < 0.001), and unplanned readmission within 30 days postoperatively (OR 1.48: 95% CI [1.15, 1.91], P = 0.002). However, this association was not consistent in the sensitivity analysis. CONCLUSIONS: Postoperative NSAIDs use was significantly associated with an increase in CR-AL incidence following PD. However, sensitivity analysis failed to show its association, which precludes a firm conclusion of its detrimental effect.

Perceptions and Experiences of Migrants in Korea Regarding Blood Donation in Association with Sociodemographic Status.

BACKGROUND: With increasing number of migrants in Korea, there is an increasing need for blood products with rare blood antigens. Accordingly, the role of blood donors among migrants has been acknowledged. We investigated migrants' experiences and perceptions of blood donation along with their sociodemographic status and identified the effects on self-reported blood donation status. METHODS: A cross-sectional survey using a self-developed, structured questionnaire was conducted on 479 migrants. The questionnaire included items about experiences, knowledge, and perceptions on blood donation and sociodemographic factors of respondents. RESULTS: Most migrants in this study were from Southeast Asia (54.7%) or China (39.9%). Among them, 28.6% (N=137) had donated blood previously, and 2.7% (N=13) had previously donated blood in Korea. All previous blood donors were volunteers, and the two major deterrents of blood donation for non-donors were the fear of pain and lack of knowledge about blood donation. In multivariable logistic regression analysis, the country of birth (odds ratio [OR]=2.65, P<0.001 [China]; OR=4.85, P=0.001 [countries other than China and Southeast Asian countries]) and employment status (OR=2.80, P=0.034) were independently associated with blood donation. CONCLUSIONS: This is the first Korean study to analyze migrants' experiences and perceptions of blood donation in relation to their sociodemographic status. Our findings can help establish blood donation policies for migrants, devise campaigns to enhance blood donation awareness, and ultimately create a pool of rare blood resources in a multicultural society.

Effect of sugammadex on the recovery of gastrointestinal motility after open pancreaticoduodenectomy: a single-center retrospective study.

BACKGROUND: This study aimed to investigate the association between sugammadex use and the occurrence of delayed passage of first flatus and oral intake tolerance following open pancreaticoduodenectomy (PD). METHODS: We reviewed consecutive patients who underwent open PD between 2015 and 2019; subsequently, they were divided into the sugammadex (group S) and neostigmine with anticholinergics (group N) groups based on the reversal agent used. We performed stabilized inverse probability of treatment weighting (IPTW) analysis to adjust for baseline differences between the groups. We compared the delayed passage of first flatus, oral intake tolerance, and other postoperative outcomes between the groups before and after IPTW. RESULTS: Of the 736 included patients, 309 (42.0%) received sugammadex. Stabilized IPTW revealed a significantly lower occurrence of delayed passage of first flatus in group S (19.3%) compared to group N (28.3%) (OR 0.61, 95% CI: 0.43-0.86, P=0.005). Further, there was a significantly lower occurrence of delayed oral intake tolerance in group S (19.9%) than in group N (27.7%) (OR 0.65, 95% CI: 0.46-0.92, P=0.016). CONCLUSIONS: Compared to previous reversal agents, sugammadex use was significantly associated with a decrease in the occurrence of prolonged time to first flatus and oral intake tolerance following open PD.

Product Inspection Methodology via Deep Learning: An Overview.

In this study, we present a framework for product quality inspection based on deep learning techniques. First, we categorize several deep learning models that can be applied to product inspection systems. In addition, we explain the steps for building a deep-learning-based inspection system in detail. Second, we address connection schemes that efficiently link deep learning models to product inspection systems. Finally, we propose an effective method that can maintain and enhance a product inspection system according to improvement goals of the existing product inspection systems. The proposed system is observed to possess good system maintenance and stability owing to the proposed methods. All the proposed methods are integrated into a unified framework and we provide detailed explanations of each proposed method. In order to verify the effectiveness of the proposed system, we compare and analyze the performance of the methods in various test scenarios. We expect that our study will provide useful guidelines to readers who desire to implement deep-learning-based systems for product inspection.