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Abstract Chimeric antigen receptor-engineered T (CAR-T) cells have shown promising efficacy in patients with relapsed/refractory B cell acute lymphoblastic leukemia (R/R B-ALL). However, challenges remain including long manufacturing processes that need to be overcome. We presented the CD19-targeting CAR-T cell product GC007F manufactured next-day (FasTCAR-T cells) and administered to patients with R/R B-ALL. A total of 21 patients over 14 years of age with CD19+ R/R B-ALL were screened, enrolled and infused with a single infusion of GC007F CAR-T at three different dose levels. The primary objective of the study was to assess safety, secondary objectives included pharmacokinetics of GC007F cells in patients with R/R B-ALL and preliminary efficacy. We were able to demonstrate in preclinical studies that GC007F cells exhibited better proliferation and tumor killing than conventional CAR-T (C-CAR-T) cells. In this investigator-initiated study all 18 efficacy-evaluable patients achieved a complete remission (CR) (18/18, 100.00%) by day 28, with 17 of the patients (94.4%) achieving CR with minimal residual disease (MRD) negative. Fifteen (83.3%) remained disease free at the 3-month assessment, 14 patients (77.8%) maintaining MRD negative at month 3. Among all 21 enrolled patients, the median peak of CAR-T cell was on day 10, with a median peak copy number of 104899.5/µg DNA and a median persistence period of 56 days (range: 7–327 days). The incidence of cytokine release syndrome (CRS) was 95.2% (n = 20), with severe CRS occurring in 52.4% (n = 11) of the patients. Six patients (28.6%) developed neurotoxicity of any grade. GC007F demonstrated superior expansion capacity and a less exhausted phenotype as compared to (C-CAR-T) cells. Moreover, this first-in-human clinical study showed that the novel, next-day manufacturing FasTCAR-T cells was feasible with a manageable toxicity profile in patients with R/R B-ALL.

A new protocol for the preparation of vinylcyclopropanecarbaldehydes as well as cyclopropylaziridines through allylic ylides is developed using readily available alpha, beta-unsaturated imines as starting materials. The high diastereoselectivity, excellent enantioselectivity, and in particular the unique chemoselectivity make this reaction potentially useful.

In a large-scale data environment, the “curse of dimensionality” of high-dimensional feature spaces and the large amount of noisy data make the efficiency and accuracy of intrusion detection systems (IDSs) significantly decrease. To address these challenges, the underlying algorithm can not only reduce dimensionality, but also remove some redundant and irrelevant noise data from the massive data. Accordingly, herein, an IDS combining deep belief network (DBN) with feature-weighted support vector machines (WSVM) is proposed. First, an adaptive learning rate strategy is applied to promote the training performance of the IDBN, which is used for learning deep features from raw data for reducing dimensionality. Second, the particle swarm optimization algorithm is used to optimize the SVM, followed by the determination of the weights of deep features and the best parameters of the Gaussian kernel, resulting in WSVM which can remove weakly related and redundant features from all IDBN-extracted features. The NSL-KDD dataset was used to validate the IDBN-WSVM model. In particular, the model performance was studied and compared to a model comprising a non-weighted SVM and other machine learning methods. Experimental results demonstrate that IDBN-WSVM is well-suited for designing high-precision classification models. The proposed improved model achieves accuracies of 85.73% and 82.36% in binary- and five-category classification experiments, respectively, which is better than or near state-of-the-art method. The IDBN-WSVM model not only saves training time and testing time on large-scale datasets, but also is more robust and has better performance of generalization than traditional methods, which provides a new research method that achieves high accuracy in intrusion detection tasks.

The present study investigated the change in the voice quality of patients with unilateral vocal fold paralysis (UVFP) of benign and malignant causes after medialization thyroplasty. Thirty-four native Cantonese adults who had been diagnosed with UVFP participated in the study. Acoustical parameters including the average voice fundamental frequency, percent jitter, relative average perturbation (RAP), percent shimmer, and noise-to-harmonic ratio (NHR) were measured from the sustained vowel /a/ that was recorded before and after the thyroplasty procedure. Maximum phonation time (MPT) was also obtained. Results indicated that, for both benign and malignant patients, all acoustical parameters except for NHR showed improvement after thyroplasty: Percent jitter, RAP, and percent shimmer values were significantly reduced, and MPT was significantly lengthened. Our findings support the notion that medialization thyroplasty is a useful palliative procedure to improve voice production in Cantonesespeaking UVFP patients. Despite the cancerous condition, it is still beneficial to malignant UVFP patients, and better voice quality can be achieved. [ABSTRACT FROM AUTHOR]

Owing to the constraints of time and space complexity, network intrusion detection systems (NIDSs) based on support vector machines (SVMs) face the “curse of dimensionality” in a large-scale, high-dimensional feature space. This study proposes a joint training model that combines a stacked autoencoder (SAE) with an SVM and the kernel approximation technique. The training model uses the SAE to perform feature dimension reduction, uses random Fourier features to perform kernel approximation, and then random Fourier mapping is explicitly applied to the sub-sample to generate the random feature space, making it possible to apply a linear SVM to uniformly approximate to the Gaussian kernel SVM. Finally, the SAE performs joint training with the efficient linear SVM. We studied the effects of an SAE structure and a random Fourier feature on classification performance, and compared that performance with that of other training models, including some without kernel approximation. At the same time, we compare the accuracy of the proposed model with that of other models, which include basic machine learning models and the state-of-the-art models in other literatures. The experimental results demonstrate that the proposed model outperforms the previously proposed methods in terms of classification performance and also reduces the training time. Our model is feasible and works efficiently on large-scale datasets.

Objectives/hypothesis: Severe acute respiratory syndrome (SARS) caused by coronavirus has become an epidemic affecting many regions worldwide. Fourteen percent to 20% of patients require endotracheal intubation and ventilator support. Some of these patients may require tracheostomy subsequently. This procedure, when performed without protection, may lead to infection of the medical and nursing staff taking care of the patient.Study Design: Based on clinical information of three patients.Methods: The authors carried out an emergency tracheostomy and changed the tracheostomy tube for one patient and performed elective tracheostomy in another two patients.Results: No medical or nursing staff member was infected after carrying out the procedure while taking all the precautions and wearing the appropriate protective apparel.Conclusion: The authors have prepared guidelines for performing a safe tracheostomy under both elective and emergency conditions. Surgeons who might be involved in performing the tracheostomy should become familiar with these guidelines and the appropriate protective apparel. [ABSTRACT FROM AUTHOR]

Introduction: OpenAI's ChatGPT, a Large Language Model (LLM), is a powerful tool across domains, designed for text and code generation, fostering collaboration, especially in public health. Investigating the role of this advanced LLM chatbot in assisting public health practitioners in shaping disease transmission models to inform infection control strategies, marks a new era in infectious disease epidemiology research. This study used a case study to illustrate how ChatGPT collaborates with a public health practitioner in co-designing a mathematical transmission model., Methods: Using natural conversation, the practitioner initiated a dialogue involving an iterative process of code generation, refinement, and debugging with ChatGPT to develop a model to fit 10 days of prevalence data to estimate two key epidemiological parameters: i) basic reproductive number (Ro) and ii) final epidemic size. Verification and validation processes are conducted to ensure the accuracy and functionality of the final model., Results: ChatGPT developed a validated transmission model which replicated the epidemic curve and gave estimates of Ro of 4.19 (95 % CI: 4.13- 4.26) and a final epidemic size of 98.3 % of the population within 60 days. It highlighted the advantages of using maximum likelihood estimation with Poisson distribution over least squares method., Conclusion: Integration of LLM in medical research accelerates model development, reducing technical barriers for health practitioners, democratizing access to advanced modeling and potentially enhancing pandemic preparedness globally, particularly in resource-constrained populations., Competing Interests: None., (© 2024 Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology.)

The recurrent multiwave nature of coronavirus disease 2019 (COVID-19) necessitates updating its symptomatology. We characterize the effect of variants on symptom presentation, identify the symptoms predictive and protective of death, and quantify the effect of vaccination on symptom development. With the COVID-19 cases reported up to August 25, 2022 in Hong Kong, an iterative multitier text-matching algorithm was developed to identify symptoms from free text. Multivariate regression was used to measure associations between variants, symptom development, death, and vaccination status. A least absolute shrinkage and selection operator technique was used to identify a parsimonious set of symptoms jointly associated with death. Overall, 70.9% (54 450/76 762) of cases were symptomatic with 102 symptoms identified. Intrinsically, the wild-type and delta variant caused similar symptoms among unvaccinated symptomatic cases, whereas the wild-type and omicron BA.2 subvariant had heterogeneous patterns, with seven symptoms (fatigue, fever, chest pain, runny nose, sputum production, nausea/vomiting, and sore throat) more frequent in the BA.2 cohort. With ≥2 vaccine doses, BA.2 was more likely than delta to cause fever among symptomatic cases. Fever, blocked nose, pneumonia, and shortness of breath remained jointly predictive of death among unvaccinated symptomatic elderly in the wild-type-to-omicron transition. Number of vaccine doses required for reducing occurrence varied by symptoms. We substantiate that omicron has a different clinical presentation compared to previous variants. Syndromic surveillance can be bettered with reduced reliance on symptom-based case identification, increased weighing on symptoms predictive of death in outcome prediction, individual-based risk assessment in care homes, and incorporating free-text symptom reporting., (© 2024 The Authors. Journal of Medical Virology published by Wiley Periodicals LLC.)

Objectives: To investigate the feasibility and performance of Chat Generative Pretrained Transformer (ChatGPT) in converting symptom narratives into structured symptom labels., Methods: We extracted symptoms from 300 deidentified symptom narratives of COVID-19 patients by a computer-based matching algorithm (the standard), and prompt engineering in ChatGPT. Common symptoms were those with a prevalence >10% according to the standard, and similarly less common symptoms were those with a prevalence of 2-10%. The precision of ChatGPT was compared with the standard using sensitivity and specificity with 95% exact binomial CIs (95% binCIs). In ChatGPT, we prompted without examples (zero-shot prompting) and with examples (few-shot prompting)., Results: In zero-shot prompting, GPT-4 achieved high specificity (0.947 [95% binCI: 0.894-0.978]-1.000 [95% binCI: 0.965-0.988, 1.000]) for all symptoms, high sensitivity for common symptoms (0.853 [95% binCI: 0.689-0.950]-1.000 [95% binCI: 0.951-1.000]), and moderate sensitivity for less common symptoms (0.200 [95% binCI: 0.043-0.481]-1.000 [95% binCI: 0.590-0.815, 1.000]). Few-shot prompting increased the sensitivity and specificity. GPT-4 outperformed GPT-3.5 in response accuracy and consistent labelling., Discussion: This work substantiates ChatGPT's role as a research tool in medical fields. Its performance in converting symptom narratives to structured symptom labels was encouraging, saving time and effort in compiling the task-specific training data. It potentially accelerates free-text data compilation and synthesis in future disease outbreaks and improves the accuracy of symptom checkers. Focused prompt training addressing ambiguous descriptions impacts medical research positively., (Copyright © 2023 European Society of Clinical Microbiology and Infectious Diseases. Published by Elsevier Ltd. All rights reserved.)

Residents in residential care homes for the elderly (RCHEs) are at high risk of severe illnesses and mortality, while staff have high exposure to intimate care activities. Addressing vaccine hesitancy is crucial to safeguard vaccine uptake in this vulnerable setting, especially amid a pandemic. In response to this, we conducted a cross-sectional survey to measure the level of vaccine hesitancy and to examine its associated factors among residents and staff in RCHEs in Hong Kong. We recruited residents and staff from 31 RCHEs in July-November 2022. Of 204 residents, 9.8% had a higher level of vaccine hesitancy (scored ≥ 4 out of 7, mean = 2.44). Around 7% of the staff ( n = 168) showed higher vaccine hesitancy (mean = 2.45). From multi-level regression analyses, higher social loneliness, higher anxiety, poorer cognitive ability, being vaccinated with fewer doses, and lower institutional vaccination rates predicted residents' vaccine hesitancy. Similarly, higher emotional loneliness, higher anxiety, being vaccinated with fewer doses, and working in larger RCHEs predicted staff's vaccine hesitancy. Although the reliance on self-report data and convenience sampling may hamper the generalizability of the results, this study highlighted the importance of addressing the loneliness of residents and staff in RCHEs to combat vaccine hesitancy. Innovative and technology-aided interventions are needed to build social support and ensure social interactions among the residents and staff, especially amid outbreaks.

Background: Antibiotics are commonly prescribed for respiratory tract infections (RTIs) among older adults in long-term care facilities (LTCFs), and this contributes to the emergence of antimicrobial resistance. The objective of this study was to determine the antibiotic prescribing rate for RTIs among LTCF residents, and to analyse the antibiotic consumption patterns with the AwaRe monitoring tool, developed by the World Health Organization., Methods: MEDLINE, EMBASE and CINAHL were searched from inception to March 2022. Original articles reporting antibiotic use for RTIs in LTCFs were included in this review. Study quality was assessed using the Joanna Briggs Institute's Critical Appraisal Checklist for Prevalence Data. A random-effects meta-analysis was employed to calculate the pooled estimates. Subgroup analysis was conducted by type of RTI, country, and study start year., Results: In total, 47 articles consisting of 50 studies were included. The antibiotic prescribing rate ranged from 21.5% to 100% (pooled estimate 69.8%, 95% confidence interval 55.2-82.6%). The antibiotic prescribing rate for lower respiratory tract infections (LRTIs) was higher than the rates for viral and general RTIs. Compared with Italy, France and the USA, the Netherlands had lower antibiotic use for LRTIs. A proportion of viral RTIs were treated with antibiotics, and all the antibiotics were from the Watch group. Use of antibiotics in the Access group was higher in the Netherlands, Norway, Switzerland and Slovenia compared with the USA and Australia., Conclusion: The antibiotic prescribing rate for RTIs in LTCFs was high, and AWaRe antibiotic use patterns varied by type of RTI and country. Improving antibiotic use may require coordination efforts., (Copyright © 2022 The Healthcare Infection Society. Published by Elsevier Ltd. All rights reserved.)

Objectives: To estimate the basic reproductive number (Ro) to help us understand and control the spread of monkeypox in immunologically naive populations., Methods: Using three highest incidence populations including England, Portugal, and Spain as examples as of 18 June 2022, we employed the branching process with a Poisson likelihood and gamma-distributed serial interval to fit daily reported case data of monkeypox to estimate Ro. Sensitivity analyses were performed by varying mean serial interval from 6.8 to 12.8 days., Results: The median posterior estimates of Ro for monkeypox in the three study populations were statistically >1 (England: Ro = 1.60 [95% (credible interval) CrI, 1.50-1.70]; Portugal: Ro = 1.40 [95% CrI, 1.20-1.60]; Spain: Ro = 1.80 [95% CrI, 1.70-2.00]). Ro estimates varied over 1.30 to 2.10, depending on the serial interval., Discussion: The updated Ro estimates across different populations will inform policy makers' plans for public health control measures. Currently, monkeypox has a sustainable outbreak potential and may challenge healthcare systems, mainly due to declines in the population level immunity to Orthopoxviruses since the cessation of routine smallpox vaccination. Smallpox vaccination has been shown to be effective in protecting (≤85% effectiveness) against monkeypox infection in earlier times. So early postexposure vaccination is currently being offered in an attempt to control its spread., (Copyright © 2022 European Society of Clinical Microbiology and Infectious Diseases. Published by Elsevier Ltd. All rights reserved.)

Background: During the early phase of the Coronavirus Disease 2019 (COVID-19) epidemic, health care workers had elevated levels of psychological distress. Historical exposure to disease outbreak may shape different pandemic responses among experienced health care workers., Aim: Considering the unique experience of the 2003 SARS outbreak in Hong Kong, this study examined the association between prior epidemic work experience and anxiety levels, and the mediating role of perceived severity of COVID-19 and SARS in nurses., Methods: In March 2020, a cross-sectional survey targeting practising nurses in Hong Kong was conducted during the early phase of the COVID-19 epidemic. The interrelationships among participants' work experience during the SARS outbreak, perceived severity of SARS and COVID-19, and anxiety level were elucidated using structural equation model (SEM)., Findings: Of 1,061 eligible nurses, a majority were female (90%) with a median age of 39 years (IQR = 32-49). A significant and negative indirect association was identified between SARS experience and anxiety levels (B=-0.04, p=0.04) in the SEM with a satisfactory fitness (CFI=0.95; RMSEA=0.06). SARS-experienced nurses perceived SARS to be less severe (B=-0.17, p=0.01), translated an equivalent perception to COVID-19 (B=1.29, p<0.001) and resulted in a lower level of anxiety (B=0.19, p<0.001)., Conclusions: The less vigorous perception towards the severity of SARS and COVID-19 may explain SARS-experienced nurses' less initial epidemic-induced anxiety. The possible role of outbreak-experienced nurses in supporting outbreak-inexperienced nurses, both emotionally and technically, should be considered when an epidemic commences. Interventions aiming to facilitate the understanding of emerging virus should also be in place., (© 2022 Australian College of Nursing Ltd. Published by Elsevier Ltd.)

Background: Amid the current COVID-19 pandemic, there is an urgent need for both vaccination and revaccination ("boosting"). This study aims to identify factors associated with the intention to receive a booster dose of the coronavirus (COVID-19) vaccine among individuals vaccinated with two doses and characterize their profiles in Hong Kong, a city with a low COVID-19 incidence in the initial epidemic waves. Among the unvaccinated, vaccination intention is also explored and their profiles are investigated., Methods: From December 2021 - January 2022, an online survey was employed to recruit 856 Hong Kong residents aged 18 years or over from an established population-based cohort. Latent class analysis and multivariate logistic regression modeling approaches were used to characterize boosting intentions., Results: Of 638 (74.5%) vaccinated among 856 eligible subjects, 42.2% intended to receive the booster dose. Four distinct profiles emerged with believers having the highest intention, followed by apathetics, fence-sitters and skeptics. Believers were older and more likely to have been vaccinated against influenza. Older age, smoking, experiencing no adverse effects from a previous COVID-19 vaccination, greater confidence in vaccines and collective responsibility, and fewer barriers in accessing vaccination services were associated with higher intentions to receive the booster dose. Of 218 unvaccinated, most were fence-sitters followed by apathetics, skeptics, and believers., Conclusion: This study foretells the booster intended uptake lagging initial vaccination across different age groups and can help refine the current or future booster vaccination campaign. Given the fourth COVID-19 vaccine dose may be offered to all adults, strategies for improving boosting uptake include policies targeting young adults, individuals who experienced adverse effects from previous doses, fence-sitters, apathetics, and the general public with low trust in the health authorities., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Kwok, Li, Leung, Tang, Chan, Tsoi, Wei, McNeil and Wong.)

Background: We have previously reported our early experience in robotic-assisted nasopharyngectomy. The current case series is a report of our experience in 33 robotic-assisted nasopharyngectomy., Methods: Prospective series of patients who underwent robotic-assisted nasopharyngectomy for local recurrent nasopharyngeal carcinoma from January 2010 to March 2019., Results: Thirty-one patients underwent robotic-assisted nasopharyngectomy with two additional second procedure for positive margin. Median age is 55 years (29-85). Twenty-five patients had rT1 disease and six patients had tumor invaded sphenoid floor (rT3). Median operative time was 227 min and median blood loss was 200 ml. The median follow-up period for all patients were 38 months. Four patients had local recurrence. Five-year local control rate, overall survival, and disease-free survival are 85.1%, 55.7%, and 69.1%, respectively., Conclusion: Robotic-assisted nasopharyngectomy for recurrent nasopharyngectomy was showed to have a high local control rate. The operating time was comparable to open surgery., (© 2022 Wiley Periodicals LLC.)

Background: Despite clear evidence of benefits in acute-care hospitals, controversy over the effectiveness of IPC measures for MDROs is perceptible and evidence-based practice has not been established., Objective: To investigate the effects of IPC interventions on MDRO colonization and infections in LTCFs., Data Sources: Ovid MEDLINE, EMBASE, and CINAHL from inception to September 2020., Eligibility Criteria: Original and peer-reviewed articles examining the post-intervention effects on MDRO colonization and infections in LTCFs., Interventions: (i) Horizontal interventions: administrative engagement, barrier precautions, education, environmental cleaning, hand hygiene, performance improvement, and source control; and (ii) vertical intervention: active surveillance plus decolonization., Study Appraisal and Synthesis: We employed a random-effects meta-analysis to estimate the pooled risk ratios (pRRs) for methicillin-resistant Staphylococcus aureus (MRSA) colonization by intervention duration; and conducted subgroup analyses on different intervention components. Study quality was assessed using Cochrane risk of bias tools., Results: Of 3877 studies identified, 19 were eligible for inclusion (eight randomized controlled trials (RCTs)). Studies reported outcomes associated with MRSA (15 studies), vancomycin-resistant Enterococci (VRE) (four studies), Clostridium difficile (two studies), and Gram-negative bacteria (GNB) (two studies). Eleven studies were included in the meta-analysis. The pRRs were close to unity regardless of intervention duration (long: RR 0.81 [95% CI 0.60-1.10]; medium: RR 0.81 [95% CI 0.25-2.68]; short: RR 0.95 [95% CI 0.53-1.69]). Vertical interventions in studies with a small sample size showed significant reductions in MRSA colonization while horizontal interventions did not. All studies involving active administrative engagement reported reductions. The risk of bias was high in all but two studies., Conclusions: Our meta-analysis did not show any beneficial effects from IPC interventions on MRSA reductions in LTCFs. Our findings highlight that the effectiveness of interventions in these facilities is likely conditional on resource availability-particularly decolonization and barrier precautions, due to their potential adverse events and uncertain effectiveness. Hence, administrative engagement is crucial for all effective IPC programmes. LTCFs should consider a pragmatic approach to reinforce standard precautions as routine practice and implement barrier precautions and decolonization to outbreak responses only., (© 2022. The Author(s).)

Introduction: Two years into the coronavirus 2019 (COVID-19) pandemic, populations with less built-up immunity continued to devise ways to optimize social distancing measures (SDMs) relaxation levels for outbreaks triggered by SARS-CoV-2 and its variants to resume minimal economics activities while avoiding hospital system collapse., Method: An age-stratified compartmental model featuring social mixing patterns was first fitted the incidence data in second wave in Hong Kong. Hypothetical scenario analysis was conducted by varying population mobility and vaccination coverages (VCs) to predict the number of hospital and intensive-care unit admissions in outbreaks initiated by ancestral strain and its variants (Alpha, Beta, Gamma, Delta and Omicron). Scenarios were "unsustainable" if either of admissions was larger than the maximum of its occupancy., Results: At VC of 65%, scenarios of full SDMs relaxation (mean daily social encounters prior to COVID-19 pandemic = 14.1 contacts) for outbreaks triggered by ancestral strain, Alpha and Beta were sustainable. Restricting levels of SDMs was required such that the optimal population mobility had to be reduced to 0.9, 0.65 and 0.37 for Gamma, Delta and Omicron associated outbreaks respectively. VC improvement from 65% to 75% and 95% allowed complete SDMs relaxation in Gamma-, and Delta-driven epidemic respectively. However, this was not supported for Omicron-triggered epidemic., Discussion: To seek a path to normality, speedy vaccine and booster distribution to the majority across all age groups is the first step. Gradual or complete SDMs lift could be considered if the hybrid immunity could be achieved due to high vaccination coverage and natural infection rate among vaccinated or the COVID-19 case fatality rate could be reduced similar to that for seasonal influenza to secure hospital system sustainability., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2022 The Authors.)

The invasion of skin tissue by Staphylococcus aureus is mediated by mechanisms that involve sequential breaching of the different stratified layers of the epidermis. Induction of cell death in keratinocytes is a measure of virulence and plays a crucial role in the infection progression. We established a 3D-organotypic keratinocyte-fibroblast co-culture model to evaluate whether a 3D-skin model is more effective in elucidating the differences in the induction of cell death by Methicillin-resistant Staphylococcus aureus (MRSA) than in comparison to 2D-HaCaT monolayers. We investigated the difference in adhesion, internalization, and the apoptotic index in HaCaT monolayers and our 3D-skin model using six strains of MRSA representing different clonal types, namely, ST8, ST30, ST59, ST22, ST45 and ST239. All the six strains exhibited internalization in HaCaT cells. Due to cell detachment, the invasion study was limited up to two and a half hours. TUNEL assay showed no significant difference in the cell death induced by the six MRSA strains in the HaCaT cells. Our 3D-skin model provided a better insight into the interactions between the MRSA strains and the human skin during the infection establishment as we could study the infection of MRSA in our skin model up to 48 h. Immunohistochemical staining together with TUNEL assay in the 3D-skin model showed co-localization of the bacteria with the apoptotic cells demonstrating the induction of apoptosis by the bacteria and revealed the variation in bacterial transmigration among the MRSA strains. The strain representing ST59 showed maximum internalization in HaCaT cells and the maximum cell death as measured by Apoptotic index in the 3D-skin model. Our results show that 3D-skin model might be more likely to imitate the physiological response of skin to MRSA infection than 2D-HaCaT monolayer keratinocyte cultures and will enhance our understanding of the difference in pathogenesis among different MRSA strains.

Background: Transmission of respiratory pathogens such as SARS-CoV-2 depends on patterns of contact and mixing across populations. Understanding this is crucial to predict pathogen spread and the effectiveness of control efforts. Most analyses of contact patterns to date have focused on high-income settings., Methods: Here, we conduct a systematic review and individual-participant meta-analysis of surveys carried out in low- and middle-income countries and compare patterns of contact in these settings to surveys previously carried out in high-income countries. Using individual-level data from 28,503 participants and 413,069 contacts across 27 surveys, we explored how contact characteristics (number, location, duration, and whether physical) vary across income settings., Results: Contact rates declined with age in high- and upper-middle-income settings, but not in low-income settings, where adults aged 65+ made similar numbers of contacts as younger individuals and mixed with all age groups. Across all settings, increasing household size was a key determinant of contact frequency and characteristics, with low-income settings characterised by the largest, most intergenerational households. A higher proportion of contacts were made at home in low-income settings, and work/school contacts were more frequent in high-income strata. We also observed contrasting effects of gender across income strata on the frequency, duration, and type of contacts individuals made., Conclusions: These differences in contact patterns between settings have material consequences for both spread of respiratory pathogens and the effectiveness of different non-pharmaceutical interventions., Funding: This work is primarily being funded by joint Centre funding from the UK Medical Research Council and DFID (MR/R015600/1)., Competing Interests: AM, OW, OR, MM, AD, PD, MK, AK, RK, SK, KK, CL, Od, KL, WM, AM, CM, JM, EN, DN, WP, FR, SS, WW, RW, JW, JZ, CW No competing interests declared, PW received funding from WHO and the Asian Development Bank via their institution to investigate COVID19 Vaccine modelling. The author has no other competing interests to declare, MA has received research funding from Seqirus outside the submitted work, CG has received funding from NIH, CDC, AHRQ, FDA, Campbell Alliance/Syneos Health and Sanofi, outside the current work. CGG has also received consulting fees from Pfizer, Merck and Sanofi. The author has no other competing interests to declare, GP was employed by the Emmes Company while analyzing the Niakhar Senegal social contact network data included in this study. The Emmes Company was contracted to perform data cleaning and data analysis of the Niakhar, Senegal clinical trial data (but not the social contact network data) for this study before GEP joined the Emmes Company (in October 2015). After GEP joined the Emmes Company, the sole support from Emmes for this manuscript was in the form of salary support for GEP. GEP also received travel support from Thomas Francis Jr. Travel Fellowship. The author has no other competing interests to declare, JS received travel support for this work from Thomas Francis, Jr. Scholarship Fund. JDS has also received consultancy fees from the International Vaccine Institute, Seoul, Republic of Korea, for work related to studies of typhoid fever burden and vaccine impact. JDS also participates on a Data Safety Monitoring Board for optimising infant immunisation schedules in Uganda & Nepal, University of Oxford, UK (ongoing), PW received consultancy fees from Pfizer for a lecture on statistical inference using infectious disease models and payment or honoraria from IS Global, Barcelona (for a lecture on statistical inference using infectious disease models) and Lancet Global Health (for reviewing an article). The author has no other competing interests to declare