Poly(N-Heterocyclic Carbene)-Capped Alloy and Core-Shell AuAg Bimetallic Nanoparticles.

N-Heterocyclic carbene (NHC)-stabilized metal nanoparticles (NPs) have recently attracted considerable attention. While most efforts in the field have been devoted to the development of NHC-tethered monometallic NPs and enhancing their stabilities under various conditions, their bimetallic counterparts are rare in the literature. Herein, we demonstrate that the covalent immobilization of Au and Ag atoms on polymerized NHCs is a powerful method to access bimetallic AuAg NPs. In addition, we show that while AuAg alloy NPs are often obtained via this method, the use of bimetallic polymeric substrates with lower Ag content, relative to Au, results in the formation of core-shell NPs with Au core and Ag shell. Application of these nanomaterials for oxygen reduction reaction is demonstrated with all materials exhibiting electrocatalytic activity. This work demonstrates for the first time that while bimetallic poly(NHC-metal)s are viable substrates to access NHC-stabilized bimetallic NPs, careful adjustment of metal content in the polymeric substrates can finetune the microstructure of the resulting NPs, i.e. alloy vs. core-shell.

Benefits and harms of cervical screening, triage and treatment strategies in women living with HIV.

To support a strategy to eliminate cervical cancer as a public health problem, the World Health Organisation (WHO) reviewed its guidelines for screening and treatment of cervical pre-cancerous lesions in 2021. Women living with HIV have 6-times the risk of cervical cancer compared to women in the general population, and we harnessed a model platform ('Policy1-Cervix-HIV') to evaluate the benefits and harms of a range of screening strategies for women living with HIV in Tanzania, a country with endemic HIV. Assuming 70% coverage, we found that 3-yearly primary HPV screening without triage would reduce age-standardised cervical cancer mortality rates by 72%, with a number needed to treat (NNT) of 38.7, to prevent a cervical cancer death. Triaging HPV positive women before treatment resulted in minimal loss of effectiveness and had more favorable NNTs (19.7-33.0). Screening using visual inspection with acetic acid (VIA) or cytology was less effective than primary HPV and, in the case of VIA, generated a far higher NNT of 107.5. These findings support the WHO 2021 recommendation that women living with HIV are screened with primary HPV testing in a screen-triage-and-treat approach starting at 25 years, with regular screening every 3-5 years.

Avian influenza A(H5) virus circulation in live bird markets in Vietnam, 2017-2022.

BACKGROUND: Highly pathogenic avian influenza A(H5) human infections are a global concern, with many A(H5) human cases detected in Vietnam, including a case in October 2022. Using avian influenza virus surveillance from March 2017-September 2022, we described the percent of pooled samples that were positive for avian influenza A, A(H5), A(H5N1), A(H5N6), and A(H5N8) viruses in live bird markets (LBMs) in Vietnam. METHODS: Monthly at each LBM, 30 poultry oropharyngeal swab specimens and five environmental samples were collected. Samples were pooled in groups of five and tested for influenza A, A(H5), A(H5N1), A(H5N6), and A(H5N8) viruses by real-time reverse-transcription polymerase chain reaction. Trends in the percent of pooled samples that were positive for avian influenza were summarized by LBM characteristics and time and compared with the number of passively detected avian influenza outbreaks using Spearman's rank correlation. RESULTS: A total of 25,774 pooled samples were collected through active surveillance at 167 LBMs in 24 provinces; 36.9% of pooled samples were positive for influenza A, 3.6% A(H5), 1.9% A(H5N1), 1.1% A(H5N6), and 0.2% A(H5N8). Influenza A(H5) viruses were identified January-December and at least once in 91.7% of sampled provinces. In 246 A(H5) outbreaks in poultry; 20.3% were influenza A(H5N1), 60.2% A(H5N6), and 19.5% A(H5N8); outbreaks did not correlate with active surveillance. CONCLUSIONS: In Vietnam, influenza A(H5) viruses were detected by active surveillance in LBMs year-round and in most provinces sampled. In addition to outbreak reporting, active surveillance for A(H5) viruses in settings with high potential for animal-to-human spillover can provide situational awareness.

Ultrathin Atomic Layer Deposited Al2O3 Overcoat Stabilizes Al2O3-Pt/Ni-Foam Hydrogenation Catalysts.

Galvanic exchange seeds the growth of Pt nanostructures on the Ni foam monolith. Subsequent atomic layer deposition of ultrathin Al2O3 followed by annealing under air affords supported Pt catalysts with ultralow loading (0.020 ppm). In addition to the expected enhancement of the stability of the Pt particles on the surface, the ∼2 nm Al2O3 overcoat appears to also play a crucial role in the overall structural integrity of the NiOx nanoplates that grow on the Ni foam surface as a result of the preparative route. The resulting material is physically robust toward repeated handling and showcases retention of catalytic activity over 10 standard catalyst recycling trials, standing in marked contrast to the uncoated samples. Catalyst activity was tested via the hydrogenation of various functionalized styrenes at low temperatures and low hydrogen pressure in ethanol as a solvent, with a TOF as high as 9.5 × 106 h-1 for unfunctionalized styrene. Notably, the catalysts show excellent tolerance toward F, Cl, and Br substituents and no hydrogenation of the aromatic ring.

Small molecule allosteric modulation of the adenosine A1 receptor.

G protein-coupled receptors (GPCRs) represent the target for approximately a third of FDA-approved small molecule drugs. The adenosine A1 receptor (A1R), one of four adenosine GPCR subtypes, has important (patho)physiological roles in humans. A1R has well-established roles in the regulation of the cardiovascular and nervous systems, where it has been identified as a potential therapeutic target for a number of conditions, including cardiac ischemia-reperfusion injury, cognition, epilepsy, and neuropathic pain. A1R small molecule drugs, typically orthosteric ligands, have undergone clinical trials. To date, none have progressed into the clinic, predominantly due to dose-limiting unwanted effects. The development of A1R allosteric modulators that target a topographically distinct binding site represent a promising approach to overcome current limitations. Pharmacological parameters of allosteric ligands, including affinity, efficacy and cooperativity, can be optimized to regulate A1R activity with high subtype, spatial and temporal selectivity. This review aims to offer insights into the A1R as a potential therapeutic target and highlight recent advances in the structural understanding of A1R allosteric modulation.

Trastuzumab deruxtecan in metastatic breast cancer with variable HER2 expression: the phase 2 DAISY trial.

The mechanisms of action of and resistance to trastuzumab deruxtecan (T-DXd), an anti-HER2-drug conjugate for breast cancer treatment, remain unclear. The phase 2 DAISY trial evaluated the efficacy of T-DXd in patients with HER2-overexpressing (n = 72, cohort 1), HER2-low (n = 74, cohort 2) and HER2 non-expressing (n = 40, cohort 3) metastatic breast cancer. In the full analysis set population (n = 177), the confirmed objective response rate (primary endpoint) was 70.6% (95% confidence interval (CI) 58.3-81) in cohort 1, 37.5% (95% CI 26.4-49.7) in cohort 2 and 29.7% (95% CI 15.9-47) in cohort 3. The primary endpoint was met in cohorts 1 and 2. Secondary endpoints included safety. No new safety signals were observed. During treatment, HER2-expressing tumors (n = 4) presented strong T-DXd staining. Conversely, HER2 immunohistochemistry 0 samples (n = 3) presented no or very few T-DXd staining (Pearson correlation coefficient r = 0.75, P = 0.053). Among patients with HER2 immunohistochemistry 0 metastatic breast cancer, 5 of 14 (35.7%, 95% CI 12.8-64.9) with ERBB2 expression below the median presented a confirmed objective response as compared to 3 of 10 (30%, 95% CI 6.7-65.2) with ERBB2 expression above the median. Although HER2 expression is a determinant of T-DXd efficacy, our study suggests that additional mechanisms may also be involved. (ClinicalTrials.gov identifier NCT04132960 .).

The application of artificial intelligence to accelerate G protein-coupled receptor drug discovery.

The application of artificial intelligence (AI) approaches to drug discovery for G protein-coupled receptors (GPCRs) is a rapidly expanding area. Artificial intelligence can be used at multiple stages during the drug discovery process, from aiding our understanding of the fundamental actions of GPCRs to the discovery of new ligand-GPCR interactions or the prediction of clinical responses. Here, we provide an overview of the concepts behind artificial intelligence, including the subfields of machine learning and deep learning. We summarise the published applications of artificial intelligence to different stages of the GPCR drug discovery process. Finally, we reflect on the benefits and limitations of artificial intelligence and share our vision for the exciting potential for further development of applications to aid GPCR drug discovery. In addition to making the drug discovery process "faster, smarter and cheaper," we anticipate that the application of artificial intelligence will create exciting new opportunities for GPCR drug discovery.

Deep learning models for forecasting dengue fever based on climate data in Vietnam.

BACKGROUND: Dengue fever (DF) represents a significant health burden in Vietnam, which is forecast to worsen under climate change. The development of an early-warning system for DF has been selected as a prioritised health adaptation measure to climate change in Vietnam. OBJECTIVE: This study aimed to develop an accurate DF prediction model in Vietnam using a wide range of meteorological factors as inputs to inform public health responses for outbreak prevention in the context of future climate change. METHODS: Convolutional neural network (CNN), Transformer, long short-term memory (LSTM), and attention-enhanced LSTM (LSTM-ATT) models were compared with traditional machine learning models on weather-based DF forecasting. Models were developed using lagged DF incidence and meteorological variables (measures of temperature, humidity, rainfall, evaporation, and sunshine hours) as inputs for 20 provinces throughout Vietnam. Data from 1997-2013 were used to train models, which were then evaluated using data from 2014-2016 by Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). RESULTS AND DISCUSSION: LSTM-ATT displayed the highest performance, scoring average places of 1.60 for RMSE-based ranking and 1.95 for MAE-based ranking. Notably, it was able to forecast DF incidence better than LSTM in 13 or 14 out of 20 provinces for MAE or RMSE, respectively. Moreover, LSTM-ATT was able to accurately predict DF incidence and outbreak months up to 3 months ahead, though performance dropped slightly compared to short-term forecasts. To the best of our knowledge, this is the first time deep learning methods have been employed for the prediction of both long- and short-term DF incidence and outbreaks in Vietnam using unique, rich meteorological features. CONCLUSION: This study demonstrates the usefulness of deep learning models for meteorological factor-based DF forecasting. LSTM-ATT should be further explored for mitigation strategies against DF and other climate-sensitive diseases in the coming years.

Presence of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Antibodies Among Vietnamese Healthcare Workers by Dosing Interval for ChAdOx1 nCoV-19 Vaccine.

BACKGROUND: Before the SARS-CoV-2 Delta variant arrived in Vietnam, case rates suggested seroprevalence of SARS-CoV-2 was low. Beginning in March 2021, we assessed different dosing schedules and adverse events following immunization (AEFIs) for ChAdOx1 nCoV-19 vaccine among healthcare workers (HCWs). METHODS: We performed a prospective cohort study to estimate the prevalence of IgG antibodies to SARS-CoV-2 before and after ChAdOx1 nCoV-19 vaccination. We conducted antibody testing among HCWs in February 2021 (baseline), before the second dose (June-July 2021), and 1 and 3 months after the second dose. We detected antibodies to SARS-CoV-2 using Tetracore® FlexImmArray™, and surrogate neutralizing antibodies using GenScript cPass™. Neither assay can distinguish natural from vaccine-induced antibodies. We assessed AEFIs through interview post-dose 1 and 1 month post-dose 2. RESULTS: Before vaccination, 1/617 participants (0.16%) had antibodies to SARS-CoV-2. Of these 617, 405 were vaccinated with ChAdOx1 nCoV-19 with 4-8- (60%), 9-12- (27%), or ≥13-week (13%) intervals between the 2 doses. Three months following series completion, 99% and 97% of vaccinated participants had ≥1 sample with detectable antibodies and surrogate neutralizing antibodies against SARS-CoV-2, respectively. We observed no significant differences among those with different dosing intervals at last follow-up. All participants reported PCR testing for SARS-CoV-2 during the study; 2 (0.5%) were laboratory-confirmed. AEFIs were more frequent post-dose 1 (81%) vs post-dose 2 (21%). CONCLUSIONS: In this population, regardless of dosing interval, ChAdOx1 nCoV-19 induced antibodies within 3 months of the second dose. These findings may offer flexibility to policymakers when balancing programmatic considerations with vaccine effectiveness.

Methods for rapid prototyping novel labware: using CAD and desktop 3D printing in the microbiology laboratory.

Although the microbiology laboratory paradigm has increasingly changed from manual to automated procedures, and from functional to molecular methods, traditional culture methods remain vital. Using inexpensive desktop fused filament fabrication 3D printing, we designed, produced and tested rapid prototypes of customised labware for microbial culture namely frames to make dip slides, inoculation loops, multi-pin replicators, and multi-well culture plates for solid medium. These customised components were used to plate out samples onto solid media in various formats, and we illustrate how they can be suitable for many microbiological methods such as minimum inhibitory concentration tests, or for directly detecting pathogens from mastitis samples, illustrating the flexibility of rapid-prototyped culture consumable parts for streamlining microbiological methods. We describe the methodology needed for microbiologists to develop their own novel and unique tools, or to fabricate and customise existing consumables. A workflow is presented for designing and 3D printing labware and quickly producing easy-to-sterilise and re-useable plastic parts of great utility in the microbiology laboratory.

Enhancement of Skin Delivery of Drugs Using Proposome Depends on Drug Lipophilicity.

The study aims to investigate the propylene glycol-based liposomes named 'proposomes' in enhancing skin permeation of drugs with different physicochemical properties. Ibuprofen, tofacitinib citrate, rhodamine B, and lidocaine were loaded into proposomes. These drug formulations were analyzed for particle size, zeta potential, polydispersity index, entrapment efficiency, and in vitro skin permeation. The confocal laser scanning microscopy was performed on skin treated with calcein and rhodamine B laden proposomes. The transdermal delivery relative to physicochemical properties of drugs such as logP, melting point, molecular weight, solubility, etc., were analyzed. We tested the safety of the proposomes using reconstructed human skin tissue equivalents, which were fabricated in-house. We also used human cadaver skin samples as a control. The proposomes had an average diameter of 128 to 148 nm. The drug's entrapment efficiencies were in the range of 42.9-52.7%, translating into the significant enhancement of drug permeation through the skin. The enhancement ratio was 1.4 to 4.0, and linearly correlated to logP, molecular weight, and melting point. Confocal imaging also showed higher skin permeation of calcein and rhodamine B in proposome than in solution. The proposome was found safe for skin application. The enhancement of skin delivery of drugs through proposomes was dependent on the lipophilicity of the drug. The entrapment efficiency was positively correlated with logP of the drug, which led to high drug absorption.

Exploring the Significance of the Exon 4-Skipping Isoform of the ZNF217 Oncogene in Breast Cancer.

Oncogene alternative splicing events can create distinct functional transcripts that offer new candidate prognostic biomarkers for breast cancer. ZNF217 is a well-established oncogene but its exon 4-skipping isoform (ZNF217-ΔE4) has never been investigated in terms of clinical or biological relevance. Using in silico RNA-seq and RT-qPCR analyses, we demonstrated for the first time the existence of ZNF217-ΔE4 transcripts in primary breast tumors, and a positive correlation between ZNF217-ΔE4 mRNA levels and those of the wild-type oncogene (ZNF217-WT). A pilot retrospective analysis revealed that, in the Luminal subclass, the combination of the two ZNF217 variants (the ZNF217-ΔE4-WT gene-expression signature) provided more information than the mRNA expression levels of each isoform alone. Ectopic overexpression of ZNF217-ΔE4 in breast cancer cells promoted an aggressive phenotype and an increase in ZNF217-WT expression levels that was inversely correlated with DNA methylation of the ZNF217 gene. This study provides new insights into the possible role of the ZNF217-ΔE4 splice variant in breast cancer and suggests a close interplay between the ZNF217-WT and ZNF217-ΔE4 isoforms. Our data suggest that a dual signature combining the expression levels of these two isoforms may serve as a novel prognostic biomarker allowing better stratification of breast cancers with good prognosis and aiding clinicians in therapeutic decisions.

Applying Machine Learning to Identify Anti-Vaccination Tweets during the COVID-19 Pandemic.

Anti-vaccination attitudes have been an issue since the development of the first vaccines. The increasing use of social media as a source of health information may contribute to vaccine hesitancy due to anti-vaccination content widely available on social media, including Twitter. Being able to identify anti-vaccination tweets could provide useful information for formulating strategies to reduce anti-vaccination sentiments among different groups. This study aims to evaluate the performance of different natural language processing models to identify anti-vaccination tweets that were published during the COVID-19 pandemic. We compared the performance of the bidirectional encoder representations from transformers (BERT) and the bidirectional long short-term memory networks with pre-trained GLoVe embeddings (Bi-LSTM) with classic machine learning methods including support vector machine (SVM) and naïve Bayes (NB). The results show that performance on the test set of the BERT model was: accuracy = 91.6%, precision = 93.4%, recall = 97.6%, F1 score = 95.5%, and AUC = 84.7%. Bi-LSTM model performance showed: accuracy = 89.8%, precision = 44.0%, recall = 47.2%, F1 score = 45.5%, and AUC = 85.8%. SVM with linear kernel performed at: accuracy = 92.3%, Precision = 19.5%, Recall = 78.6%, F1 score = 31.2%, and AUC = 85.6%. Complement NB demonstrated: accuracy = 88.8%, precision = 23.0%, recall = 32.8%, F1 score = 27.1%, and AUC = 62.7%. In conclusion, the BERT models outperformed the Bi-LSTM, SVM, and NB models in this task. Moreover, the BERT model achieved excellent performance and can be used to identify anti-vaccination tweets in future studies.

Quantitative Analysis of Colistin-Resistant Escherichia coli in Retail Meat from Local Vietnamese Markets.

The spread of drug-resistant bacteria via food has contributed to the dissemination of resistant bacteria among humans. However, the status of food contamination with resistant bacteria, particularly the quantitative level of resistant bacteria in food, has not yet been well elucidated. In this study, the abundance of colistin-resistant Escherichia coli in meat samples was quantified to understand the origin of the contamination of meat available in local Vietnamese markets. Fifteen samples each of chicken and pork meat purchased from local Vietnamese markets were assessed for the presence of colistin-resistant E. coli with the mobile colistin resistance gene, mcr. The results showed that 40% (6/15) and 66% (10/15) of the pork and chicken meat samples, respectively, were contaminated with colistin-resistant E. coli. The median quantitative levels of colistin-resistant E. coli in the contaminated pork and chicken samples were 1.8 × 104 and 4.2 × 103 CFU/g, respectively. The results of phylogenetic analysis of isolates from a chicken meat sample showed that the contaminated colistin-resistant E. coli was a mix of multiple phylogenetical clones of bacteria that may have multiplied during sale. This is the first study to quantify the abundance of colistin-resistant E. coli in meat samples.

Proposome for transdermal delivery of tofacitinib.

Tofacitinib citrate (TC) has recently gained interest in treating skin disorders such as psoriasis, atopic dermatitis and baldness. Unfortunately, the oral administration shows side effects, such as decreased neutrophil counts. To this end, the topical delivery of TC can be used to reduce the risk associated with systemic exposure. However, TC shows minimal absorption via skin. Hence, the objective of this study is to enhance the skin delivery of TC using a non-invasive approach. The liposomes based on propylene glycol, named as proposomes, carrying TC, were studied. The vesicle characteristics and in vitro skin permeation were assessed. The proposomes enhanced the skin permeability of TC by 4-11 folds. The composition of proposomes was found to affect the skin permeation and deposition of TC. The proposomes were stable for at least 6 months. Overall, proposomes were effective for targeted topical drug delivery.

Impact of HPV vaccination and cervical screening on cervical cancer elimination: a comparative modelling analysis in 78 low-income and lower-middle-income countries.

BACKGROUND: The WHO Director-General has issued a call for action to eliminate cervical cancer as a public health problem. To help inform global efforts, we modelled potential human papillomavirus (HPV) vaccination and cervical screening scenarios in low-income and lower-middle-income countries (LMICs) to examine the feasibility and timing of elimination at different thresholds, and to estimate the number of cervical cancer cases averted on the path to elimination. METHODS: The WHO Cervical Cancer Elimination Modelling Consortium (CCEMC), which consists of three independent transmission-dynamic models identified by WHO according to predefined criteria, projected reductions in cervical cancer incidence over time in 78 LMICs for three standardised base-case scenarios: girls-only vaccination; girls-only vaccination and once-lifetime screening; and girls-only vaccination and twice-lifetime screening. Girls were vaccinated at age 9 years (with a catch-up to age 14 years), assuming 90% coverage and 100% lifetime protection against HPV types 16, 18, 31, 33, 45, 52, and 58. Cervical screening involved HPV testing once or twice per lifetime at ages 35 years and 45 years, with uptake increasing from 45% (2023) to 90% (2045 onwards). The elimination thresholds examined were an average age-standardised cervical cancer incidence of four or fewer cases per 100 000 women-years and ten or fewer cases per 100 000 women-years, and an 85% or greater reduction in incidence. Sensitivity analyses were done, varying vaccination and screening strategies and assumptions. We summarised results using the median (range) of model predictions. FINDINGS: Girls-only HPV vaccination was predicted to reduce the median age-standardised cervical cancer incidence in LMICs from 19·8 (range 19·4-19·8) to 2·1 (2·0-2·6) cases per 100 000 women-years over the next century (89·4% [86·2-90·1] reduction), and to avert 61·0 million (60·5-63·0) cases during this period. Adding twice-lifetime screening reduced the incidence to 0·7 (0·6-1·6) cases per 100 000 women-years (96·7% [91·3-96·7] reduction) and averted an extra 12·1 million (9·5-13·7) cases. Girls-only vaccination was predicted to result in elimination in 60% (58-65) of LMICs based on the threshold of four or fewer cases per 100 000 women-years, in 99% (89-100) of LMICs based on the threshold of ten or fewer cases per 100 000 women-years, and in 87% (37-99) of LMICs based on the 85% or greater reduction threshold. When adding twice-lifetime screening, 100% (71-100) of LMICs reached elimination for all three thresholds. In regions in which all countries can achieve cervical cancer elimination with girls-only vaccination, elimination could occur between 2059 and 2102, depending on the threshold and region. Introducing twice-lifetime screening accelerated elimination by 11-31 years. Long-term vaccine protection was required for elimination. INTERPRETATION: Predictions were consistent across our three models and suggest that high HPV vaccination coverage of girls can lead to cervical cancer elimination in most LMICs by the end of the century. Screening with high uptake will expedite reductions and will be necessary to eliminate cervical cancer in countries with the highest burden. FUNDING: WHO, UNDP, UN Population Fund, UNICEF-WHO-World Bank Special Program of Research, Development and Research Training in Human Reproduction, Canadian Institute of Health Research, Fonds de recherche du Québec-Santé, Compute Canada, National Health and Medical Research Council Australia Centre for Research Excellence in Cervical Cancer Control.

Mortality impact of achieving WHO cervical cancer elimination targets: a comparative modelling analysis in 78 low-income and lower-middle-income countries.

BACKGROUND: WHO is developing a global strategy towards eliminating cervical cancer as a public health problem, which proposes an elimination threshold of four cases per 100 000 women and includes 2030 triple-intervention coverage targets for scale-up of human papillomavirus (HPV) vaccination to 90%, twice-lifetime cervical screening to 70%, and treatment of pre-invasive lesions and invasive cancer to 90%. We assessed the impact of achieving the 90-70-90 triple-intervention targets on cervical cancer mortality and deaths averted over the next century. We also assessed the potential for the elimination initiative to support target 3.4 of the UN Sustainable Development Goals (SDGs)-a one-third reduction in premature mortality from non-communicable diseases by 2030. METHODS: The WHO Cervical Cancer Elimination Modelling Consortium (CCEMC) involves three independent, dynamic models of HPV infection, cervical carcinogenesis, screening, and precancer and invasive cancer treatment. Reductions in age-standardised rates of cervical cancer mortality in 78 low-income and lower-middle-income countries (LMICs) were estimated for three core scenarios: girls-only vaccination at age 9 years with catch-up for girls aged 10-14 years; girls-only vaccination plus once-lifetime screening and cancer treatment scale-up; and girls-only vaccination plus twice-lifetime screening and cancer treatment scale-up. Vaccination was assumed to provide 100% lifetime protection against infections with HPV types 16, 18, 31, 33, 45, 52, and 58, and to scale up to 90% coverage in 2020. Cervical screening involved HPV testing at age 35 years, or at ages 35 years and 45 years, with scale-up to 45% coverage by 2023, 70% by 2030, and 90% by 2045, and we assumed that 50% of women with invasive cervical cancer would receive appropriate surgery, radiotherapy, and chemotherapy by 2023, which would increase to 90% by 2030. We summarised results using the median (range) of model predictions. FINDINGS: In 2020, the estimated cervical cancer mortality rate across all 78 LMICs was 13·2 (range 12·9-14·1) per 100 000 women. Compared to the status quo, by 2030, vaccination alone would have minimal impact on cervical cancer mortality, leading to a 0·1% (0·1-0·5) reduction, but additionally scaling up twice-lifetime screening and cancer treatment would reduce mortality by 34·2% (23·3-37·8), averting 300 000 (300 000-400 000) deaths by 2030 (with similar results for once-lifetime screening). By 2070, scaling up vaccination alone would reduce mortality by 61·7% (61·4-66·1), averting 4·8 million (4·1-4·8) deaths. By 2070, additionally scaling up screening and cancer treatment would reduce mortality by 88·9% (84·0-89·3), averting 13·3 million (13·1-13·6) deaths (with once-lifetime screening), or by 92·3% (88·4-93·0), averting 14·6 million (14·1-14·6) deaths (with twice-lifetime screening). By 2120, vaccination alone would reduce mortality by 89·5% (86·6-89·9), averting 45·8 million (44·7-46·4) deaths. By 2120, additionally scaling up screening and cancer treatment would reduce mortality by 97·9% (95·0-98·0), averting 60·8 million (60·2-61·2) deaths (with once-lifetime screening), or by 98·6% (96·5-98·6), averting 62·6 million (62·1-62·8) deaths (with twice-lifetime screening). With the WHO triple-intervention strategy, over the next 10 years, about half (48% [45-55]) of deaths averted would be in sub-Saharan Africa and almost a third (32% [29-34]) would be in South Asia; over the next 100 years, almost 90% of deaths averted would be in these regions. For premature deaths (age 30-69 years), the WHO triple-intervention strategy would result in rate reductions of 33·9% (24·4-37·9) by 2030, 96·2% (94·3-96·8) by 2070, and 98·6% (96·9-98·8) by 2120. INTERPRETATION: These findings emphasise the importance of acting immediately on three fronts to scale up vaccination, screening, and treatment for pre-invasive and invasive cervical cancer. In the next 10 years, a one-third reduction in the rate of premature mortality from cervical cancer in LMICs is possible, contributing to the realisation of the 2030 UN SDGs. Over the next century, successful implementation of the WHO elimination strategy would reduce cervical cancer mortality by almost 99% and save more than 62 million women's lives. FUNDING: WHO, UNDP, UN Population Fund, UNICEF-WHO-World Bank Special Program of Research, Development and Research Training in Human Reproduction, Germany Federal Ministry of Health, National Health and Medical Research Council Australia, Centre for Research Excellence in Cervical Cancer Control, Canadian Institute of Health Research, Compute Canada, and Fonds de recherche du Québec-Santé.

Leader Humility and Knowledge Sharing Intention: A Serial Mediation Model.

PURPOSE: This paper examines the influence of leader humility on knowledge sharing intention. Drawing on social exchange theory (SET), we test the direct and indirect mechanisms to explain the influence leader humility has on knowledge sharing intention. DESIGN/METHODOLOGY/APPROACH: A two-wave, time-lagged field study was conducted. We surveyed 252 professional employees from Australia. FINDINGS: Results show a significant direct, positive association between leader humility and knowledge sharing intention. While leader humility had a direct, positive association with affective trust in supervisor and work engagement, it did not directly impact on organizational citizenship behaviors directed toward the individual (OCB-I). There were three SET-related, serial mediators in the relationship between leader humility and knowledge sharing intention. These were affective trust, work engagement, and OCB-I. RESEARCH LIMITATIONS/IMPLICATIONS: Future studies should collect multi-source data such as peers' or supervisors' ratings of the focal respondents' work engagement, OCB-I, and knowledge sharing behaviors to augment single-source data. Future studies could adopt an affect theory of social exchange to further explore the relationships tested in this study. ORIGINALITY/VALUE: This study contributes to the affect SET and knowledge management literature on how leadership behaviors impact the intention to share knowledge. Our study highlights the preference of the willingness to share knowledge with their co-workers is mediated by affective trust in their immediate supervisors, work engagement, and OCB-I that are equally important as treating their subordinates with humility.

Cuticle and pore plug properties in the table egg.

Food safety of table eggs is vital since many pathogens can contaminate the unfertilized egg, leading to increased risk of foodborne illness for consumers. The eggshell cuticle is the first line of defense to restrict the entry of egg-associated pathogens, such as Salmonella Enteritidis. The thickness and completeness of coverage of the cuticle layer are heritable traits that are strongly associated with egg resistance to bacterial penetration. The present study characterizes the chemical composition of the eggshell cuticle and structure of pore plugs from table eggs. Eggs collected from both brown and white egg laying Lohmann flocks (early, mid, and late lay) were either unwashed or washed. Pore plugs were characterized using scanning electron microscopy (SEM), and elemental composition was determined using energy-dispersive x-ray spectroscopy (EDS). SEM observations confirmed that the plug formed by the cuticle layer within the eggshell pore remains firmly lodged throughout the commercial washing process. The eggshell thickness and cuticle pore length visualized in brown eggs was significantly higher than in white eggs in hens of all ages. EDS analysis revealed that the pore inner surface was enriched in phosphorus and chemically different from the surrounding bulk eggshell mineral. Detailed assessment of the cuticle chemical composition was performed by Fourier transform infrared spectroscopy (FTIR). Washing of eggs removed cuticle from the eggshell surface. There was a trend of lower cuticle coverage with increasing hen age for white eggs. A significant reduction in the amount of proteins and phosphates and polysaccharides was observed in the cuticle of brown unwashed eggs with hen age. In white unwashed eggs, amides and lipids decreased with hen age; by contrast, the amount of sulfate was highest at mid-lay. The results from our research will assist selective breeding programs that target cuticle integrity and pore plug stability to enhance egg resistance to pathogen penetration and improve food safety.

Activation of a Plant NLR Complex through Heteromeric Association with an Autoimmune Risk Variant of Another NLR.

When independently evolved immune receptor variants meet in hybrid plants, they can activate immune signaling in the absence of non-self recognition. Such autoimmune risk alleles have recurrently evolved at the DANGEROUS MIX2 (DM2) nucleotide-binding domain and leucine-rich repeat (NLR)-encoding locus in A. thaliana. One of these activates signaling in the presence of a particular variant encoded at another NLR locus, DM1. We show that the risk variants of DM1 and DM2d NLRs signal through the same pathway that is activated when plant NLRs recognize non-self elicitors. This requires the P loops of each protein and Toll/interleukin-1 receptor (TIR)-domain-mediated heteromeric association of DM1 and DM2d. DM1 and DM2d each resides in a multimeric complex in the absence of signaling, with the DM1 complex shifting to higher molecular weight when heteromerizing DM2 variants are present. The activation of the DM1 complex appears to be sensitive to the conformation of the heteromerizing DM2 variant. Autoimmunity triggered by interaction of this NLR pair thus suggests that activity of heteromeric NLR signaling complexes depends on the sum of activation potentials of partner NLRs.