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When a second-rate cage fighter, Luke Wright, is tormented by the Russian Mafia and wanders the streets of New York, he witnesses a young Chinese girl, Mei, being pursued by the same mafia who want her for a priceless numerical code that they would kill for.

Hospital surfaces are known to contribute to the spread of healthcare-associated antimicrobial pathogens. Environmental sampling can help locate reservoirs and determine intervention strategies, although sampling and detection can be labor intensive. Composite approaches may help reduce time and costs associated with sampling and detection. We investigated optimum surface areas for sampling antimicrobial-resistant organisms (AROs) with a single side of cellulose sponge, created theoretical composites (TC) by adding recovery results from multiple optimum areas, then compared the TC to the standard Centers for Disease Control and Prevention sampling method (one sponge using all sides, whole tool; (WT)). Five AROs were evaluated: carbapenemase-producing KPC+ Klebsiella pneumoniae (KPC), Acinetobacter baumannii (AB), methicillin-resistant Staphylococcus aureus (MRSA), vancomycin-resistant Enterococcus faecalis (VRE) and Clostridioides difficile spores (CD). Steel coupons comprising four surface areas (323; 645; 1,290 and 2,258 cm 2 ) were inoculated, dried, and sampled with one sampling pass using the larger side (face) or the smaller side (edge) of a pre-moistened cellulose sponge tool. Based on the optimum areas determined for each organism, composite areas were 1,290 cm 2 for MRSA and VRE, 1,936 cm 2 for AB, 2,580 cm 2 for CD spores and 3,870 cm 2 for KPC. Total colony forming units (CFU) recovered using a composite approach was greater or comparable than using multiple WT samplings (over the same area as the composite) for MRSA, VRE and AB (130%; 144% and 95%) yet less than if using multiple WT samplings for KP and CD (47% and 66%). We propose a conservative composite sampling strategy if the target organism is unknown; 323 cm 2 sampling area for each of the four sides of the sponge, (1290 cm 2 total). The conservative composite sampling strategy improved the recovery of KP (from 47% to 85% of multiple WT samplings), while MRSA, VRE, AB and CD (131%; 144%; 97% and 66%) remained within 5% to that of the optimum area TC.

In May 2019, we investigated monkeypox in a traveler from Nigeria to Singapore. The public health response included rapid identification of contacts, use of quarantine, and postexposure smallpox vaccination. No secondary cases were identified. Countries should develop surveillance systems to detect emerging infectious diseases globally.

Abstract Background Rapid identification of COVID-19 cases, which is crucial to outbreak containment efforts, is challenging due to the lack of pathognomonic symptoms and in settings with limited capacity for specialized nucleic acid–based reverse transcription polymerase chain reaction (PCR) testing. Methods This retrospective case-control study involves subjects (7–98 years) presenting at the designated national outbreak screening center and tertiary care hospital in Singapore for SARS-CoV-2 testing from 26 January to 16 February 2020. COVID-19 status was confirmed by PCR testing of sputum, nasopharyngeal swabs, or throat swabs. Demographic, clinical, laboratory, and exposure-risk variables ascertainable at presentation were analyzed to develop an algorithm for estimating the risk of COVID-19. Model development used Akaike’s information criterion in a stepwise fashion to build logistic regression models, which were then translated into prediction scores. Performance was measured using receiver operating characteristic curves, adjusting for overconfidence using leave-one-out cross-validation. Results The study population included 788 subjects, of whom 54 (6.9%) were SARS-CoV-2 positive and 734 (93.1%) were SARS-CoV-2 negative. The median age was 34 years, and 407 (51.7%) were female. Using leave-one-out cross-validation, all the models incorporating clinical tests (models 1, 2, and 3) performed well with areas under the receiver operating characteristic curve (AUCs) of 0.91, 0.88, and 0.88, respectively. In comparison, model 4 had an AUC of 0.65. Conclusions Rapidly ascertainable clinical and laboratory data could identify individuals at high risk of COVID-19 and enable prioritization of PCR testing and containment efforts. Basic laboratory test results were crucial to prediction models. A risk score incorporating easily ascertainable demographic, clinical evaluation, and clinical testing covariates to identify patients at high risk of COVID-19 can help prioritize subjects for testing and public health measures to prevent onward transmission, especially in resource-limited settings.

The proportion of asymptomatic carriers and transmission risk factors of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) among household and non-household contacts remains unclear. In Singapore, extensive contact tracing by the Ministry of Health for every diagnosed COVID-19 case, and legally enforced quarantine and intensive health surveillance of close contacts provided a rare opportunity to determine asymptomatic attack rates and SARS-CoV-2 transmission risk factors among community close contacts of patients with COVID-19. This retrospective cohort study involved all close contacts of confirmed COVID-19 cases in Singapore, identified between Jan 23 and April 3, 2020. Household contacts were defined as individuals who shared a residence with the index COVID-19 case. Non-household close contacts were defined as those who had contact for at least 30 min within 2 m of the index case. All patients with COVID-19 in Singapore received inpatient treatment, with access restricted to health-care staff. All close contacts were quarantined for 14 days with thrice-daily symptom monitoring via telephone. Symptomatic contacts underwent PCR testing for SARS-CoV-2. Secondary clinical attack rates were derived from the prevalence of PCR-confirmed SARS-CoV-2 among close contacts. Consenting contacts underwent serology testing and detailed exposure risk assessment. Bayesian modelling was used to estimate the prevalence of missed diagnoses and asymptomatic SARS-CoV-2-positive cases. Univariable and multivariable logistic regression models were used to determine SARS-CoV-2 transmission risk factors. Between Jan 23 and April 3, 2020, 7770 close contacts (1863 household contacts, 2319 work contacts, and 3588 social contacts) linked to 1114 PCR-confirmed index cases were identified. Symptom-based PCR testing detected 188 COVID-19 cases, and 7582 close contacts completed quarantine without a positive SARS-CoV-2 PCR test. Among 7518 (96·8%) of the 7770 close contacts with complete data, the secondary clinical attack rate was 5·9% (95% CI 4·9–7·1) for 1779 household contacts, 1·3% (0·9–1·9) for 2231 work contacts, and 1·3% (1·0–1·7) for 3508 social contacts. Bayesian analysis of serology and symptom data obtained from 1150 close contacts (524 household contacts, 207 work contacts, and 419 social contacts) estimated that a symptom-based PCR-testing strategy missed 62% (95% credible interval 55–69) of COVID-19 diagnoses, and 36% (27–45) of individuals with SARS-CoV-2 infection were asymptomatic. Sharing a bedroom (multivariable odds ratio [OR] 5·38 [95% CI 1·82–15·84]; p=0·0023) and being spoken to by an index case for 30 min or longer (7·86 [3·86–16·02]; p<0·0001) were associated with SARS-CoV-2 transmission among household contacts. Among non-household contacts, exposure to more than one case (multivariable OR 3·92 [95% CI 2·07–7·40], p<0·0001), being spoken to by an index case for 30 min or longer (2·67 [1·21–5·88]; p=0·015), and sharing a vehicle with an index case (3·07 [1·55–6·08]; p=0·0013) were associated with SARS-CoV-2 transmission. Among both household and non-household contacts, indirect contact, meal sharing, and lavatory co-usage were not independently associated with SARS-CoV-2 transmission. Targeted community measures should include physical distancing and minimising verbal interactions. Testing of all household contacts, including asymptomatic individuals, is warranted. Ministry of Health of Singapore, National Research Foundation of Singapore, and National Natural Science Foundation of China.

Data on travelers returning from areas with many cases of Covid-19 may be useful in estimating incidence. The authors report follow-up data on 94 persons who boarded an evacuation flight from Wuhan, China, to Singapore on January 30, 2020.

Flocked and foam swabs were used to sample five healthcare pathogens from three sizes of steel and plastic coupons; 26 cm2, 323 cm2, and 645 cm2. As surface area increased, 1–2 log10 decrease in recovered organisms (P < .05) was observed. Sampling 26-cm2 yielded the optimal median percent of pathogens recovered.

Regenerative stem cell‐based therapies for bronchopulmonary dysplasia (BPD), the most common preterm birth complication, demonstrate promise in animals. Failure to objectively appraise available preclinical data and identify knowledge gaps could jeopardize clinical translation. We performed a systematic review and network meta‐analysis (NMA) of preclinical studies testing cell‐based therapies in experimental neonatal lung injury. Fifty‐three studies assessing 15 different cell‐based therapies were identified: 35 studied the effects of mesenchymal stromal cells (MSCs) almost exclusively in hyperoxic rodent models of BPD. Exploratory NMAs, for select outcomes, suggest that MSCs are the most effective therapy. Although a broad range of promising cell‐based therapies has been assessed, few head‐to‐head comparisons and unclear risk of bias exists. Successful clinical translation of cell‐based therapies demands robust preclinical experimental design with appropriately blinded, randomized, and statistically powered studies, based on biological plausibility for a given cell product, in standardized models and endpoints with transparent reporting.

Background Breast cancer (BC) grading plays a critical role in patient management despite the considerable inter- and intra-observer variability, highlighting the need for decision support tools to improve reproducibility and prognostic accuracy for use in clinical practice. The objective was to evaluate the ability of a digital artificial intelligence (AI) assay (PDxBr) to enrich BC grading and improve risk categorization for predicting recurrence. Methods In our population-based longitudinal clinical development and validation study, we enrolled 2075 patients from Mount Sinai Hospital with infiltrating ductal carcinoma of the breast. With 3:1 balanced training and validation cohorts, patients were retrospectively followed for a median of 6 years. The main outcome was to validate an automated BC phenotyping system combined with clinical features to produce a binomial risk score predicting BC recurrence at diagnosis. Results The PDxBr training model ( n  = 1559 patients) had a C-index of 0.78 (95% CI, 0.76–0.81) versus clinical 0.71 (95% CI, 0.67–0.74) and image feature models 0.72 (95% CI, 0.70–0.74). A risk score of 58 (scale 0–100) stratified patients as low or high risk, hazard ratio (HR) 5.5 (95% CI 4.19–7.2, p  < 0.001), with a sensitivity 0.71, specificity 0.77, NPV 0.95, and PPV 0.32 for predicting BC recurrence within 6 years. In the validation cohort ( n  = 516), the C-index was 0.75 (95% CI, 0.72–0.79) versus clinical 0.71 (95% CI 0.66–0.75) versus image feature models 0.67 (95% CI, 0.63–071). The validation cohort had an HR of 4.4 (95% CI 2.7–7.1, p  < 0.001), sensitivity of 0.60, specificity 0.77, NPV 0.94, and PPV 0.24 for predicting BC recurrence within 6 years. PDxBr also improved Oncotype Recurrence Score (RS) performance: RS 31 cutoff, C-index of 0.36 (95% CI 0.26–0.45), sensitivity 37%, specificity 48%, HR 0.48, p  = 0.04 versus Oncotype RS plus AI-grade C-index 0.72 (95% CI 0.67–0.79), sensitivity 78%, specificity 49%, HR 4.6, p  < 0.001 versus Oncotype RS plus PDxBr, C-index 0.76 (95% CI 0.70–0.82), sensitivity 67%, specificity 80%, HR 6.1, p  < 0.001. Conclusions PDxBr is a digital BC test combining automated AI-BC prognostic grade with clinical–pathologic features to predict the risk of early-stage BC recurrence. With future validation studies, we anticipate the PDxBr model will enrich current gene expression assays and enhance treatment decision-making.