Emergence and dissemination of multidrug-resistant Escherichia coli ST8346 coharboring blaNDM-5 and blaOXA-181 in Southern Taiwan, 2017-2021.

BACKGROUND: Enterobacterales carrying blaNDM represent an emerging challenge in treating infectious diseases. In this study, we aimed to investigate the characteristics of blaNDM-producing Enterobacterales from three hospitals in southern Taiwan. METHODS: Enterobacterales strains that were nonsusceptible to more than one carbapenem (ertapenem, meropenem, imipenem, or doripenem) were collected from hospitalized patients. Molecular typing for New Delhi metallo-ß-lactamase (NDM) and antibiotic susceptibility tests were performed, followed by multilocus sequence typing (MLST), pulsed-field gel electrophoresis (PFGE), and plasmid analysis by PCR-based replicon typing. RESULTS: A total of 1311 carbapenem-nonsusceptible Enterobacterales were isolated from 2017 to 2021. blaNDM-encoding genes were detected in 108 isolates, with 53 (49.1%) harboring blaNDM-1 and 55 (50.9%) harboring blaNDM-5. The rate of blaNDM-1 detection among isolates decreased to 2% in 2021. However, the rate of E. coli harboring blaNDM-5 increased from 1% to 12% of total isolates during the study period. Of 47 NDM-5-positive E. coli isolates, 44 (93.6%) were ST8346 with high genetic relatedness. E. coli ST8346 isolates showed high-level resistance to both carbapenems and aminoglycosides. Most (38 out of 47, 80.9%) blaNDM-5-harboring E. coli isolates co-harbored blaOXA-181. We analyzed the regions harboring blaNDM-5 in E. coli ST8346 via PCR amplification. blaNDM-5 and blaOXA-181 were located on two separate plasmids, IncF and IncX3, respectively. CONCLUSION: The dissemination of E. coli ST8346 caused an increase in blaNDM-5 and blaOXA-181 co-harboring Enterobacterales in southern Taiwan, which show high-level resistance to both carbapenems and aminoglycosides. We identified a distinct IncF plasmid encoding blaNDM-5 that has the potential for rapid spread and needs further surveillance.

Antimicrobial Susceptibility of E. coli Isolates from Intra-Abdominal Infections in the Asia-Pacific Region: Trends in Ciprofloxacin, Ceftriaxone, Cefepime, and Piperacillin/Tazobactam Susceptibility.

Purpose: To investigate the antibiotic susceptibility of Escherichia coli isolates in patients diagnosed with intra-abdominal infections (IAIs) in the Asia-Pacific region. Patients and Methods: This study was conducted at 50 medical hospitals across 9 countries/regions as part of the Study for Monitoring Antimicrobial Resistance Trends (SMART) surveillance program from 2014 to 2018. Nonduplicate isolates of aerobic and facultative gram-negative bacilli were collected and processed for further antimicrobial susceptibility testing. Results: A total of 10,709 isolates were collected, with E. coli (n=4737, 44.2%) being the leading pathogen causing IAIs, followed by Klebsiella pneumoniae (n=2429, 22.7%) and Pseudomonas aeruginosa (n=931, 8.7%). Community-associated (CA) E. coli isolates generally exhibited higher susceptibility rates for most antibiotics than hospital-associated (HA) isolates. In countries/regions other than Hong Kong, South Korea, and Singapore, HA isolates displayed lower susceptibility rates for multiple classes (≥4) of antibiotics. Among the commonly used antibiotics in IAIs, the overall susceptibility rate for ciprofloxacin was low, with an average of 41.3%. Ceftriaxone susceptibility rates in all selected countries were below 80% starting in 2018, ranging from 23.3% to 75.8%. The cefepime susceptibility rates varied across regions, with consistently reduced susceptibility ranging from 45.5% to 57.8% in India, Thailand, and Vietnam. Piperacillin/tazobactam demonstrated effectiveness against E. coli isolates in almost all countries except India, with a downward trend observed in the Philippines and Taiwan. Carbapenems remained effective against more than 90% of E. coli isolates, except in India. Conclusion: Prudent use of fluoroquinolones and ceftriaxone is advised when treating both CA and HA IAIs in the Asia-Pacific region. The low susceptibility rate of cefepime in India, Thailand, and Vietnam needs careful consideration in its administration. Moreover, the increase in nonsusceptibility to piperacillin/tazobactam in the Philippines and Taiwan poses a potential risk that should be closely monitored.

Two-tiered deep-learning-based model for histologic diagnosis of Helicobacter gastritis.

AIMS: Helicobacter pylori (HP) infection is the most common cause of chronic gastritis worldwide. Due to the small size of HP and limited resolution, diagnosing HP infections is more difficult when using digital slides. METHODS AND RESULTS: We developed a two-tier deep-learning-based model for diagnosing HP gastritis. A whole-slide model was trained on 885 whole-slide images (WSIs) with only slide-level labels (positive or negative slides). An auxiliary model was trained on 824 areas with HP in nine positive WSIs and 446 negative WSIs for localizing HP. The whole-slide model performed well, with an area under the receiver operating characteristic curve (AUC) of 0.9739 (95% confidence interval [CI], 0.9545-0.9932). The calculated sensitivity and specificity were 93.3% and 90.1%, respectively, whereas those of pathologists were 93.3% and 84.2%, respectively. Using the auxiliary model, the highlighted areas of the localization maps had an average precision of 0.5796. CONCLUSIONS: HP gastritis can be diagnosed on haematoxylin-and-eosin-stained WSIs with human-level accuracy using a deep-learning-based model trained on slide-level labels and an auxiliary model for localizing HP and confirming the diagnosis. This two-tiered model can shorten the diagnostic process and reduce the need for special staining.

In vitro activities of antimicrobial combinations against planktonic and biofilm forms of Stenotrophomonas maltophilia.

Objectives: To investigate the in vitro activity of antibiotic combinations against Stenotrophomonas maltophilia isolates and their associated biofilms. Methods: Thirty-two S. maltophilia clinical isolates with at least twenty-five different pulsotypes were tested. The antibacterial activity of various antibiotic combinations against seven randomly selected planktonic and biofilm-embedded S. maltophilia strains with strong biofilm formation was assessed using broth methods. Extraction of bacterial genomic DNA and PCR detection of antibiotic resistance and biofilm-related genes were also performed. Results: The susceptibility rates of levofloxacin (LVX), fosfomycin (FOS), tigecycline (TGC) and sulfamethoxazole-trimethoprim (SXT) against 32 S. maltophilia isolates were 56.3, 71.9, 71.9 and 90.6%, respectively. Twenty-eight isolates were detected with strong biofilm formation. Antibiotic combinations, including aztreonam-clavulanic (ATM-CLA) with LVX, ceftazidime-avibactam (CZA) with LVX and SXT with TGC, exhibited potent inhibitory activity against these isolates with strong biofilm formation. The antibiotic resistance phenotype might not be fully caused by the common antibiotic-resistance or biofilm-formation gene. Conclusion: S. maltophilia remained resistant to most antibiotics, including LVX and ß-lactam/ß-lactamases; however, TGC, FOS and SXT still exhibited potent activity. Although all tested S. maltophilia isolates exhibited moderate-to-strong biofilm formation, combination therapies, especially ATM-CLA with LVX, CZA with LVX and SXT with TGC, exhibited a higher inhibitory activity for these isolates.

The effect of Lactobacillus with prebiotics on KPC-2-producing Klebsiella pneumoniae.

Objectives: This study investigated the inhibitory effect of Lactobacillus spp. with prebiotics against Klebsiella pneumoniae carbapenemase-2 (KPC-2)-producing Klebsiella pneumoniae using both in vitro experiments and animal models. Methods: Thirty-three Lactobacillus spp. strains were confirmed by 16S rDNA sequencing, and four different PFGE genotyped KPC-2-producing K. pneumoniae strains were selected for investigation. In vitro studies, including broth microdilution assays, changes in pH values in lactobacilli cultures with different prebiotics, time-kill tests of Lactobacillus spp. against KPC-2-producing K. pneumoniae and further in vivo Lactobacillus alone or in combination with prebiotics against KPC-2-producing K. pneumoniae in an animal model, were performed. Results: The lower pH value of the cell-free supernatant was associated with a lower minimal inhibitory percentage of the Lactobacillus strain against KPC-2-producing K. pneumoniae. Furthermore, lactulose/isomalto-oligosaccharide/inulin and fructo-oligosaccharide can enhance the inhibitory effect of all 107 CFU/ml Lactobacillus strains against KPC001. Three Lactobacillus strains (LYC1154, LYC1322, and LYC1511) that could be persistently detected in the stool were tested for their ability to reduce the amount of KPC001 in the feces individually or in combination. A significantly better effect in reducing the amount of KPC001 was observed for the combination of three different Lactobacillus species than for each of them alone. Furthermore, their inhibitory effect was enhanced after adding lactulose or isomalto-oligosaccharide (both p < 0.05). Conclusion: This study demonstrates the inhibitory effect of probiotic Lactobacillus, including LYC1154, LYC1322, and LYC1511, with prebiotics such as lactulose or isomalto-oligosaccharide against the colonization of KPC-2-producing K. pneumoniae.

Deep neural network trained on gigapixel images improves lymph node metastasis detection in clinical settings.

The pathological identification of lymph node (LN) metastasis is demanding and tedious. Although convolutional neural networks (CNNs) possess considerable potential in improving the process, the ultrahigh-resolution of whole slide images hinders the development of a clinically applicable solution. We design an artificial-intelligence-assisted LN assessment workflow to facilitate the routine counting of metastatic LNs. Unlike previous patch-based approaches, our proposed method trains CNNs by using 5-gigapixel images, obviating the need for lesion-level annotations. Trained on 5907 LN images, our algorithm identifies metastatic LNs in gastric cancer with a slide-level area under the receiver operating characteristic curve (AUC) of 0.9936. Clinical experiments reveal that the workflow significantly improves the sensitivity of micrometastasis identification (81.94% to 95.83%, P < .001) and isolated tumor cells (67.95% to 96.15%, P < .001) in a significantly shorter review time (-31.5%, P < .001). Cross-site evaluation indicates that the algorithm is highly robust (AUC = 0.9829).

Effects of Tocilizumab on Adults With COVID-19 Pneumonia: A Meta-Analysis.

Background: Coronavirus disease-2019 (COVID-19), a worldwide disaster, has already affected lots of people. Effective care and therapy are currently being evaluated in full swing. Purpose: Our purpose was to investigate the effects of tocilizumab, an interleukin-6 receptor inhibitor, on treatment of adult patients with COVID-19 pneumonia. Data Sources Study Selection and Data Extraction: We conducted a meta-analysis and searched for relevant studies on Pubmed, Embase, and the Cochrane Library without restrictions on language from inception until February 1, 2021. Fifteen studies were included for this meta-analysis. Two authors independently selected and screened these studies, assessed the quality of included studies, and extracted related information. Results: Fifteen studies were included in this meta-analysis. The main studies showed that tocilizumab was associated with lower mortality (risk ratio = 0.62, 95% confidence interval = 0.46-0.83; and hazard ratio = 0.61, 95% confidence interval = 0.51-0.72). Using tocilizumab might also affect biochemistry indicators (lowered C-reactive protein and ferritin, increased lymphocyte count). Conclusion: These current bodies of evidence could indicate that early use of tocilizumab was associated with lower mortality in adult patients with COVID-19. Early use of tocilizumab could reduce the mortality rate of adult patients with COVID-19 without obvious fatal side effects, which may be a treatment option in patients with COVID-19 pneumonia. Systematic Review Registration: The study protocol was registered on PROSPERO (ID:242811).

Circulating pediatric respiratory pathogens in Taiwan during 2020: Dynamic change under low COVID-19 incidence.

BACKGROUND: In Taiwan, there were only 799 confirmed COVID-19 cases in 2020. The unique backdrop amidst a pandemic and promotion of nonpharmaceutical interventions generated some distinct changes in the epidemiology of common respiratory pathogens. In this study, we aimed to investigate the dynamic changes in respiratory pathogens in children during 2020. METHODS: We performed a retrospective cohort study at a tertiary hospital in southern Taiwan during 2020. Patients aged 0-18 years who visited the pediatric emergency department were enrolled. Children who presented with clinical symptoms (fever or respiratory illness) and received nasopharyngeal swabs for multiplex polymerase chain reaction (PCR) were included in our analysis. We also compared respiratory syncytial virus (RSV) trends from previous years by PCR and lateral flow immunochromatographic assays from 2017 to 2020. RESULTS: A total of 120 children were tested. The overall detection rate was 55%. With strengthened restrictions, the detection rate dropped from 70% to 30%. However, non-enveloped viruses (rhinovirus/enterovirus and adenovirus) were in constant circulation. Upon easing prevention measures, the detection rate remained above 60%, and an outbreak of an enveloped virus (RSV and parainfluenza virus) was noted. Compared with 2017-2019, the cyclical RSV epidemic was delayed, with a large surge in late 2020. CONCLUSIONS: We observed a constant circulation of non-enveloped viruses when strict nonpharmaceutical interventions were employed and a delayed surge of enveloped viruses during the easing of restrictions. Continuous surveillance and monitoring of the evolutionary dynamics of respiratory viruses is important, while easing restrictions requires balanced judgment.

Distribution of ß-lactamases and emergence of carbapenemases co-occurring Enterobacterales isolates with high-level antibiotic resistance identified from patients with intra-abdominal infection in the Asia-Pacific region, 2015-2018.

PURPOSE: In this study, we aimed to assess the geographic distribution and molecular characteristics of ß-lactamases among Enterobacterales isolates causing intra-abdominal infections (IAIs) from 2015 to 2018 in the Asia-Pacific region. METHOD: Isolates were investigated for extended-spectrum ß-lactamases (ESBLs), AmpC ß-lactamases, and carbapenemases using multiplex PCR assays and full-gene DNA sequencing. RESULT: A total of 832 Enterobacterales isolates from 8 different countries with ß-lactamase genes were analysed. Plasmid-mediated ESBLs and AmpC ß-lactamases were encoded in 598 (71.9 %) and 314 (37.7 %) isolates, respectively. In 710 (85.3 %) carbapenemase-negative isolates, positivity for both AmpC ß-lactamases and ESBLs was identified in 51 (8.5 %) Escherichia coli and 24 (3.4 %) Klebsiella pneumoniae isolates. The most prevalent countries were Taiwan and Vietnam, and the co-occurrence of CMY/CTX-M in E. coli and DHA-1/ESBLs in K. pneumoniae was predominant. All isolates showed high susceptibility to colistin, but susceptibility to carbapenems varied among different resistance mechanism combinations. Among 122 (14.7 %) isolates encoding carbapenemase, NDM (n = 67, including 64.2 % NDM-1) was the most common, followed by the OXA-48-type (n = 49), KPC (n = 24) and IMP (n = 4). The most prevalent country was Thailand (n = 44), followed by Vietnam (n = 35) and the Philippines (n = 21). Twenty-two isolates were found to encode multiple carbapenemases, 16 of which were collected from Thailand and harbored NDM-1, OXA-232 and CTX-M-15. Despite high susceptibility to amikacin, susceptibility to colistin was only 56 %. CONCLUSION: The emergence of carbapenem-non-susceptible AmpC/ESBL co-occurring Enterobacterales and colistin non-susceptible carbapenemases co-occurring K. pneumoniae highlights potential therapeutic challenges in the Asia-Pacific region.

Improvement of p-Type AlGaN Conductivity with an Alternating Mg-Doped/Un-Doped AlGaN Layer Structure.

Using molecular beam epitaxy, we prepared seven p-type AlGaN samples of ~25% in Al content, including six samples with Mg-doped/un-doped AlGaN alternating-layer structures of different layer-thickness combinations, for comparing their p-type performances. Lower sheet resistance and higher effective hole mobility are obtained in a layer-structured sample, when compared with the reference sample of uniform Mg doping. The improved p-type performance in a layer-structured sample is attributed to the diffusion of holes generated in an Mg-doped layer into the neighboring un-doped layers, in which hole mobility is significantly higher because of weak ionized impurity scattering. Among the layer-structured samples, that of 6/4 nm in Mg-doped/un-doped thickness results in the lowest sheet resistance (the highest effective hole mobility), which is 4.83 times lower (4.57 times higher) when compared with the sample of uniform doping. The effects of the Mg-doped/un-doped layer structure on p-type performance in AlGaN and GaN are compared.

Identification of nodal micrometastasis in colorectal cancer using deep learning on annotation-free whole-slide images.

Detection of nodal micrometastasis (tumor size: 0.2-2.0 mm) is challenging for pathologists due to the small size of metastatic foci. Since lymph nodes with micrometastasis are counted as positive nodes, detecting micrometastasis is crucial for accurate pathologic staging of colorectal cancer. Previously, deep learning algorithms developed with manually annotated images performed well in identifying micrometastasis of breast cancer in sentinel lymph nodes. However, the process of manual annotation is labor intensive and time consuming. Multiple instance learning was later used to identify metastatic breast cancer without manual annotation, but its performance appears worse in detecting micrometastasis. Here, we developed a deep learning model using whole-slide images of regional lymph nodes of colorectal cancer with only a slide-level label (either a positive or negative slide). The training, validation, and testing sets included 1963, 219, and 1000 slides, respectively. A supercomputer TAIWANIA 2 was used to train a deep learning model to identify metastasis. At slide level, our algorithm performed well in identifying both macrometastasis (tumor size > 2.0 mm) and micrometastasis with an area under the receiver operating characteristics curve (AUC) of 0.9993 and 0.9956, respectively. Since most of our slides had more than one lymph node, we then tested the performance of our algorithm on 538 single-lymph node images randomly cropped from the testing set. At single-lymph node level, our algorithm maintained good performance in identifying macrometastasis and micrometastasis with an AUC of 0.9944 and 0.9476, respectively. Visualization using class activation mapping confirmed that our model identified nodal metastasis based on areas of tumor cells. Our results demonstrate for the first time that micrometastasis could be detected by deep learning on whole-slide images without manual annotation.

Molecular characteristics and in vitro effects of antimicrobial combinations on planktonic and biofilm forms of Elizabethkingia anophelis.

OBJECTIVES: To investigate the in vitro activity of antibiotics against clinical Elizabethkingia anophelis isolates and to find a suitable antibiotic combination with synergistic effects to combat antibiotic-resistant E. anophelis and its associated biofilm. METHODS: E. anophelis isolates were identified by 16S rRNA sequencing; 30 strains with different pulsotypes were identified and the MIC, antibiotic resistance mechanism, antibiotic combination activity and killing effects of antimicrobial agents on biofilms of these strains were determined. RESULTS: All E. anophelis isolates were susceptible to minocycline and cefoperazone/sulbactam (1:1). More than 90% of clinical isolates were susceptible to cefoperazone/sulbactam (1:0.5), piperacillin/tazobactam and rifampicin. Some novel mutations, such as gyrA G81D, parE D585N and parC P134T, that have never been reported before, were identified. The synergistic effect was most prominent for the combination of minocycline and rifampicin, with 93.3% of their FIC index values ≤0.5, and no antagonism was observed using the chequerboard method. This synergistic effect between minocycline and rifampicin was also observed using time-killing methods for clinical E. anophelis isolates at both normal inoculum and high inoculum. Twenty-nine isolates tested positive for biofilm formation. Minocycline remained active against biofilm-embedded and biofilm-released planktonic E. anophelis cells; however, the enhanced effect of minocycline by adding rifampicin was only observed at 24 h (not at 72 and 120 h). CONCLUSIONS: Although E. anophelis was resistant to many antibiotics and could exhibit biofilm formation, minocycline showed potent in vitro activity against this pathogen and its associated biofilm.

An annotation-free whole-slide training approach to pathological classification of lung cancer types using deep learning.

Deep learning for digital pathology is hindered by the extremely high spatial resolution of whole-slide images (WSIs). Most studies have employed patch-based methods, which often require detailed annotation of image patches. This typically involves laborious free-hand contouring on WSIs. To alleviate the burden of such contouring and obtain benefits from scaling up training with numerous WSIs, we develop a method for training neural networks on entire WSIs using only slide-level diagnoses. Our method leverages the unified memory mechanism to overcome the memory constraint of compute accelerators. Experiments conducted on a data set of 9662 lung cancer WSIs reveal that the proposed method achieves areas under the receiver operating characteristic curve of 0.9594 and 0.9414 for adenocarcinoma and squamous cell carcinoma classification on the testing set, respectively. Furthermore, the method demonstrates higher classification performance than multiple-instance learning as well as strong localization results for small lesions through class activation mapping.

Antimicrobial ability and mechanism analysis of Lactobacillus species against carbapenemase-producing Enterobacteriaceae.

BACKGROUND: This study aims to investigate the antimicrobial ability and mechanism analysis of Lactobacillus species against carbapenemase-producing Enterobacteriaceae (CPE). METHODS: Five Lactobacillus spp. strains and 18 CPE clinical isolates were collected. Their anti-CPE effects were assessed by agar well diffusion and broth microdilution assay, as well as time-kill test. Finally, the specific anti-CPE mechanism, especially for the effect of organic acids was determined using broth microdilution method. RESULTS: All of five Lactobacilli isolates displayed the potent activity against most CPE isolates with mean zones of inhibition ranging 10.2-21.1 mm. The anti-CPE activity was not affected by heating, catalase, and proteinase treatment. Under the concentration of 50% LUC0180 cell-free supernatant (CFS), lactic acid, and mix acid could totally inhibit the growth of carbapenem-resistant Klebsiella pneumoniae (CPE0011), and acetic acid could inhibit 67.8%. In contrast, succinic acid and citric acid could not inhibit the growth of CPE0011. While we decreased the concentration to 25%, only lactic acid and mix acid displayed 100% inhibition. In contrast, succinic acid, citric acid and acetic acid did not show any inhibitory effect. CONCLUSIONS: Lactobacillus strains exhibit potent anti-CPE activity, and lactic acid produced by Lactobacillus strains is the major antimicrobial mechanism.

Establishing Validity for a Vaginal Hysterectomy Simulation Model for Surgical Skills Assessment.

OBJECTIVE: To use the Messick validity framework for a simulation-based assessment of vaginal hysterectomy skills. METHODS: Video recordings of physicians at different levels of training and experience performing vaginal hysterectomy on a high-fidelity vaginal surgery model were objectively assessed using a modified 10-item Vaginal Surgical Skills Index, a one-item global scale of overall performance, and a pass-fail criterion. Participants included obstetrics and gynecology trainees and faculty from five institutions. Video recordings were independently assessed by expert surgeons blinded to the identities of the study participants. RESULTS: Fifty surgeons (11 faculty, 39 trainees) were assessed. Experience level correlated strongly with both the modified Vaginal Surgical Skills Index and global scale score, with more experienced participants receiving higher scores (Pearson r=0.81, P<.001; Pearson r=0.74, P<.001). Likewise, surgical experience was also moderately correlated with the modified Vaginal Surgical Skills Index and global scale score (Pearson r=0.55, P<.001; Pearson r=0.58, P<.001). The internal consistency of the modified Vaginal Surgical Skills Index was excellent (Cronbach's alpha=0.97). Interrater reliability of the modified Vaginal Surgical Skills Index and global scale score, as measured by the intraclass correlation coefficient, was moderate to good (0.49-0.95; 0.50-0.87). Using the receiver operating characteristic curve and the pass-fail criterion, a modified Vaginal Surgical Skills Index cutoff score of 27 was found to most accurately (area under the curve 0.951, 95% CI 0.917-0.983) differentiate competent from noncompetent surgeons. CONCLUSION: We demonstrated validity evidence for using a high-fidelity vaginal surgery model with the modified Vaginal Surgical Skills Index or global scale score to assess vaginal hysterectomy skills.

Tourism under the Early Phase of COVID-19 in Four APEC Economies: An Estimation with Special Focus on SARS Experiences.

This study examines how experience of severe acute respiratory syndrome (SARS) influences the impact of coronavirus disease (COVID-19) on international tourism demand for four Asia-Pacific Economic Cooperation (APEC) economies, Taiwan, Hong Kong, Thailand, and New Zealand, over the 1 January-30 April 2020 period. To proceed, panel regression models are first applied with a time-lag effect to estimate the general effects of COVID-19 on daily tourist arrivals. In turn, the data set is decomposed into two nation groups and fixed effects models are employed for addressing the comparison of the pandemic-tourism relationship between economies with and without experiences of the SARS epidemic. Specifically, Taiwan and Hong Kong are grouped as economies with SARS experiences, while Thailand and New Zealand are grouped as countries without experiences of SARS. The estimation result indicates that the number of confirmed COVID-19 cases has a significant negative impact on tourism demand, in which a 1% COVID-19 case increase causes a 0.075% decline in tourist arrivals, which is a decline of approximately 110 arrivals for every additional person infected by the coronavirus. The negative impact of COVID-19 on tourist arrivals for Thailand and New Zealand is found much stronger than for Taiwan and Hong Kong. In particular, the number of tourist arrivals to Taiwan and Hong Kong decreased by 0.034% in response to a 1% increase in COVID-19 confirmed cases, while in Thailand and New Zealand, a 1% national confirmed cases increase caused a 0.103% reduction in tourism demand. Moreover, the effect of the number of domestic cases on international tourism is found lower than the effect caused by global COVID-19 mortality for the economies with SARS experiences. In contrast, tourist arrivals are majorly affected by the number of confirmed COVID-19 cases in Thailand and New Zealand. Finally, travel restriction in all cases is found to be the most influencing factor for the number of tourist arrivals. Besides contributing to the existing literature focusing on the knowledge regarding the nexus between tourism and COVID-19, the paper's findings also highlight the importance of risk perception and the need of transmission prevention and control of the epidemic for the tourism sector.

UvrY is required for the full virulence of Aeromonas dhakensis.

Aeromonas dhakensis is an emerging human pathogen which causes fast and severe infections worldwide. Under the gradual pressure of lacking useful antibiotics, finding a new strategy against A. dhakensis infection is urgent. To understand its pathogenesis, we created an A. dhakensis AAK1 mini-Tn10 transposon library to study the mechanism of A. dhakensis infection. By using a Caenorhabditis elegans model, we established a screening platform for the purpose of identifying attenuated mutants. The uvrY mutant, which conferred the most attenuated toxicity toward C. elegans, was identified. The uvrY mutant was also less virulent in C2C12 fibroblast and mice models, in line with in vitro results. To further elucidate the mechanism of UvrY in controlling the toxicity in A. dhakensis, we conducted a transcriptomic analysis. The RNAseq results showed that the expression of a unique hemolysin ahh1 and other virulence factors were regulated by UvrY. Complementation of Ahh1, one of the most important virulence factors, rescued the pore-formation phenotype of uvrY mutant in C. elegans; however, complementation of ahh1 endogenous promoter-driven ahh1 could not produce Ahh1 and rescue the virulence in the uvrY mutant. These findings suggest that UvrY is required for the expression of Ahh1 in A. dhakensis. Taken together, our results suggested that UvrY controls several different virulence factors and is required for the full virulence of A. dhakensis. The two-component regulator UvrY therefore a potential therapeutic target which is worthy of further study.

In Vitro Synergy of Pongamia pinnata Extract in Combination with Antibiotics for Inhibiting and Killing Methicillin-Resistant Staphylococcus aureus.

AIMS: Currently, we face the serious problem of multiple drug-resistant pathogens. The development of new antimicrobial agents is very costly and time-consuming. Therefore, the use of medicinal plants as a source of alternative antibiotics or for enhancing antibiotic effectiveness is important. METHODS: The antibacterial effects of aqueous extracts of the seed coat of Pongamia pinnata (Linn.) Pierre in combination with several antibiotics against methicillin-resistant Staphylococcus aureus (MRSA) were tested by broth dilution, checkerboard, and time-kill methods. RESULTS: For the combinations of P. pinnata with ampicillin, meropenem, cefazolin, cefotaxime, cefpirome, and cefuroxime, 70% to 100% were synergistic, with a fractional inhibitory concentration (FIC) index of < 0.5. For the time-kill method with 0.5× minimum inhibitory concentration (MIC) of P. pinnata in combination with 8, 4, 2, and 1 µg mL-1 of the various antibiotics, almost all of the combinations showed synergistic effects, even with the lowest concentrations of P. pinnata, except for aztreonam. No antagonistic effect was observed for these combinations. CONCLUSIONS: Based on these findings, aqueous seed coat extracts of P. pinnata have good potential for the design of new antimicrobial agents.

Estimating the Threshold Effects of Climate on Dengue: A Case Study of Taiwan.

Climate change is regarded as one of the major factors enhancing the transmission intensity of dengue fever. In this study, we estimated the threshold effects of temperature on Aedes mosquito larval index as an early warning tool for dengue prevention. We also investigated the relationship between dengue vector index and dengue epidemics in Taiwan using weekly panel data for 17 counties from January 2012 to May 2019. To achieve our goals, we first applied the panel threshold regression technique to test for threshold effects and determine critical temperature values. Data were then further decomposed into different sets corresponding to different temperature regimes. Finally, negative binomial regression models were applied to assess the non-linear relationship between meteorological factors and Breteau index (BI). At the national level, we found that a 1°C temperature increase caused the expected value of BI to increase by 0.09 units when the temperature is less than 27.21 °C, and by 0.26 units when the temperature is greater than 27.21 °C. At the regional level, the dengue vector index was more sensitive to temperature changes because double threshold effects were found in the southern Taiwan model. For southern Taiwan, as the temperature increased by 1°C, the expected value of BI increased by 0.29, 0.63, and 1.49 units when the average temperature was less than 27.27 °C, between 27.27 and 30.17 °C, and higher than 30.17 °C, respectively. In addition, the effects of precipitation and relative humidity on BI became stronger when the average temperature exceeded the thresholds. Regarding the impacts of climate change on BI, our results showed that the potential effects on BI range from 3.5 to 54.42% under alternative temperature scenarios. By combining threshold regression techniques with count data regression models, this study provides evidence of threshold effects between climate factors and the dengue vector index. The proposed threshold of temperature could be incorporated into the implementation of public health measures and risk prediction to prevent and control dengue fever in the future.