We evaluated HIV DNA levels in individuals who received long-acting cabotegravir (CAB-LA) or tenofovir disoproxil fumarate/emtricitabine (TDF/FTC) pre-exposure prophylaxis in the HPTN 083 and 084 trials and had HIV DNA testing performed to help determine HIV status. HIV DNA testing was performed using peripheral blood mononuclear cell (PBMC) samples collected after a reactive HIV test was obtained at a study site. DNA was quantified using droplet digital PCR (lower limit of detection [LLOD]: 4.09 copies/million PBMCs). Final HIV status and the timing of the first HIV-positive visit were determined by an independent adjudication committee based on HIV test results from real-time site testing and retrospective testing at a centralized laboratory. HIV DNA testing was performed for 133 participants [21 HIV-positive (7 CAB-LA arm, 14 TDF/FTC arm) and 112 HIV-negative; 1-6 tests/person]. For persons with HIV, the time between the first HIV-positive visit and collection of the first sample for DNA testing was a median of 81 days for those receiving CAB-LA (range 41-246) and 11 days for those receiving TDF/FTC (range 3-127). Four (57.1%) of the seven CAB-LA cases with infection had a low initial DNA result [three detected <LLOD; one near the LLOD (4.2 copies/10(6) PBMCs); in 2/4 cases, the DNA level was still <10 copies/10(6) PBMCs ≥40 weeks after the first HIV-positive visit. In contrast, only 3/14 (21.4%) of the TDF/FTC cases had a low or negative initial DNA test result (one not detected; two <10 copies/10(6) PBMCs). In this study, the time between the first HIV-positive visit and the first DNA test was longer in the CAB-LA cases than the TDF/FTC cases. Despite this difference, low or undetectable DNA levels were more frequently observed in the CAB-LA cases. This suggests that CAB-LA exposure may limit seeding of the HIV reservoir in early infection.

BACKGROUND: Tuberculosis (TB) infection prevention and control (IPC) in healthcare facilities is key to reducing transmission risk. A framework for systematically improving TB IPC through training and mentorship was implemented in 9 healthcare facilities in China from 2017 to 2019. METHODS: Facilities conducted standardized TB IPC assessments at baseline and quarterly thereafter for 18 months. Facility-based performance was assessed using quantifiable indicators for IPC core components and administrative, environmental, and respiratory protection controls, and as a composite of all control types We calculated the percentage changes in scores over time and differences by IPC control type and facility characteristics. RESULTS: Scores for IPC core components increased by 72% during follow-up when averaged across facilities. The percentage changes for administrative, environmental, and respiratory protection controls were 39%, 46%, and 30%, respectively. Composite scores were 45% higher after the intervention. Overall, scores increased most during the first 6 months. There was no association between IPC implementation and provincial economic development or volume of TB services. CONCLUSIONS: TB IPC policies and practices showed most improvement early during implementation and did not differ consistently by facility characteristics. The training component of the project helped increase the capacity of healthcare professionals to manage TB transmission risks. Lessons learned here will inform national TB IPC guidance.

To support efforts to vaccinate millions of Americans across the United States (US) against COVID-19, the US federal government (USG) launched the Pharmacy Partnership for Long-Term Care Program (PPP) in December 2020 and the Federal Retail Pharmacy Program (FRPP) in February 2021. These programs consisted of a collaborative partnership with the USG and 21 pharmacy organizations, including large retail chains, coordinating pharmacy services administrative organizations (PSAOs) representing independent retail and long-term care pharmacies, and pharmacy network administrators. These pharmacy organizations represented over 46,000 providers and created a robust channel for far-reaching COVID-19 vaccination across 56 state and local jurisdictions. PPP reported more than 8 million COVID-19 doses administered to residents and staff in long-term care facilities (LTCFs) as of June 2021. In addition, FRPP was responsible for administering more than 304 million doses, accounting for approximately 49% of all COVID-19 doses administered as of June 2023. This unprecedented public-private partnership allowed USG to rapidly adapt, expand, and aim to provide equitable access to vaccines for adults and eligible-aged children during the COVID-19 pandemic. As the largest federal COVID-19 vaccination program, the FRPP exemplifies how public-private partnerships can expand access to immunizations during a public health emergency. End-to-end informatics support helped pharmacies meet critical national public health goals and served as convenient access points for sustained health services. This manuscript describes lessons learned regarding informatics coordination with participating pharmacy partners to support the rapid and safe administration of COVID-19 vaccines across the US. The processes of onboarding to CDC's complex data network, establishing connections to state and local immunization information systems (IIS), and monitoring the quality of data pharmacy partners submitted to the CDC Data Clearinghouse (DCH) in alignment with the COVID-19 Vaccine Reporting Specifications (CVRS) are highlighted.

Cryptosporidium ubiquitum is an emerging zoonotic pathogen. In the past, it was not possible to identify an association between cases of human and animal infection. We conducted a genomic survey of the species, developed a subtyping tool targeting the 60-kDa glycoprotein (gp60) gene, and identified 6 subtype families (XIIa-XIIf) of C. ubiquitum. Host adaptation was apparent at the gp60 locus; subtype XIIa was found in ruminants worldwide, subtype families XIIb-XIId were found in rodents in the United States, and XIIe and XIIf were found in rodents in the Slovak Republic. Humans in the United States were infected with isolates of subtypes XIIb-XIId, whereas those in other areas were infected primarily with subtype XIIa isolates. In addition, subtype families XIIb and XIId were detected in drinking source water in the United States. Contact with C. ubiquitum-infected sheep and drinking water contaminated by infected wildlife could be sources of human infections.

Machine-learning methods in the form of Bayesian networks (BN), linear projection (LP) and self-organizing tree (SOT) models were used to explore association among polymorphic sites within the HVR1 and NS5a regions of the HCV genome, host demographic factors (ethnicity, gender and age) and response to the combined interferon (IFN) and ribavirin (RBV) therapy. The BN models predicted therapy outcomes, gender and ethnicity with accuracy of 90%, 90% and 88.9%, respectively. The LP and SOT models strongly confirmed associations of the HVR1 and NS5A structures with response to therapy and demographic host factors identified by BN. The data indicate host specificity of HCV evolution and suggest the application of these models to predict outcomes of IFN/RBV therapy.

INTRODUCTION: Traditional survey-based surveillance is costly, limited in its ability to distinguish diabetes types and time-consuming, resulting in reporting delays. The Diabetes in Children, Adolescents and Young Adults (DiCAYA) Network seeks to advance diabetes surveillance efforts in youth and young adults through the use of large-volume electronic health record (EHR) data. The network has two primary aims, namely: (1) to refine and validate EHR-based computable phenotype algorithms for accurate identification of type 1 and type 2 diabetes among youth and young adults and (2) to estimate the incidence and prevalence of type 1 and type 2 diabetes among youth and young adults and trends therein. The network aims to augment diabetes surveillance capacity in the USA and assess performance of EHR-based surveillance. This paper describes the DiCAYA Network and how these aims will be achieved. METHODS AND ANALYSIS: The DiCAYA Network is spread across eight geographically diverse US-based centres and a coordinating centre. Three centres conduct diabetes surveillance in youth aged 0-17 years only (component A), three centres conduct surveillance in young adults aged 18-44 years only (component B) and two centres conduct surveillance in components A and B. The network will assess the validity of computable phenotype definitions to determine diabetes status and type based on sensitivity, specificity, positive predictive value and negative predictive value of the phenotypes against the gold standard of manually abstracted medical charts. Prevalence and incidence rates will be presented as unadjusted estimates and as race/ethnicity, sex and age-adjusted estimates using Poisson regression. ETHICS AND DISSEMINATION: The DiCAYA Network is well positioned to advance diabetes surveillance methods. The network will disseminate EHR-based surveillance methodology that can be broadly adopted and will report diabetes prevalence and incidence for key demographic subgroups of youth and young adults in a large set of regions across the USA.

From December 2020 through March 2023, the COVID-19 vaccination efforts in long-term care (LTC) settings, identified many gaps and opportunities to improve public health capacity to support vaccine distribution, education, and documentation of COVID-19 vaccines administered to LTC residents and staff. Partner engagement at the local, state, and federal levels helped establish pathways for dissemination of information, improve access and delivery of vaccines, and expand reporting of vaccine administration data to monitor the impact of COVID-19 vaccination in LTC settings. Sustaining the improvements to the vaccine infrastructure in LTC settings that were created or enhanced during the COVID-19 vaccination efforts is critical for the protection of residents and staff against COVID-19 and other vaccine preventable respiratory outbreaks in the future.

AIMS: To quantify the incremental health and economic burden associated with cognitive impairment (CI) among non-institutionalized people with diabetes ≥65 years in the United States. MATERIALS AND METHODS: Using 2016-2019 Medical Expenditure Panel Surveys data, we identified participants ≥65 years with diabetes. We used propensity score weighting to quantify the CI-associated incremental burden on health-related quality of life measured by the 12-item Short Form Survey (SF-12), including the mental component summary score, physical component summary score and health utility. We also compared the annual health service utilization and expenditures on ambulatory visits, prescriptions, home care, emergency room (ER), hospitalizations and total annual direct medical expenditures. RESULTS: We included 5094 adults aged ≥65 with diabetes, of whom 804 had CI. After propensity score weighting, CI was associated with a lower mental component summary score (-8.4, p < .001), physical component summary score (-5.2, p < .001) and health utility (-0.12, p < .001). The CI group had more ambulatory visits (+4.4, p = .004) and prescriptions (+9.9, p < .001), with higher probabilities of having home care (+11.3%, p < .001) and ER visits (+8.2%, p = .001). People with CI spent $5441 (p < .001) more annually, $2039 (p = .002) more on prescriptions, $2695 (p < .001) more on home care and $118 (p < .001) more on ER visits. There is no statistically significant difference in the utilization and expenditure of hospitalizations. CONCLUSION: CI was associated with worse health-related quality of life, higher health service utilization and expenditures. Our findings can be used to monitor the health and economic burden of CI in non-institutionalized older persons with diabetes.

The globular head domain of influenza virus surface protein hemagglutinin (HA1) is the major target of neutralizing antibodies elicited by vaccines. As little as one amino acid substitution in the HA1 can result in an antigenic drift of influenza viruses, indicating the dominance of some epitopes in the binding of HA to polyclonal serum antibodies. Therefore, identifying dominant binding epitopes of HA is critical for selecting seasonal influenza vaccine viruses. In this study, we have developed a biolayer interferometry (BLI)-based assay to determine dominant binding epitopes of the HA1 in antibody response to influenza vaccines using a panel of recombinant HA1 proteins of A(H1N1)pdm09 virus with each carrying a single amino acid substitution. Sera from individuals vaccinated with the 2010-2011 influenza trivalent vaccines were analyzed for their binding to the HA1 panel and hemagglutination inhibition (HI) activity against influenza viruses with cognate mutations. Results revealed an over 50% reduction in the BLI binding of several mutated HA1 compared to the wild type and a strong correlation between dominant residues identified by the BLI and HI assays. Our study demonstrates a method to systemically analyze antibody immunodominance in the humoral response to influenza vaccines.

Breast cancer treatment can be improved with biomarkers for early detection and individualized therapy. A set of 86 microRNAs (miRNAs) were identified to separate breast cancer tumors from normal breast tissues (n = 52) with an overall accuracy of 90.4%. Six miRNAs had concordant expression in both tumors and breast cancer patient blood samples compared with the normal control samples. Twelve miRNAs showed concordant expression in tumors vs. normal breast tissues and patient survival (n = 1093), with seven as potential tumor suppressors and five as potential oncomiRs. From experimentally validated target genes of these 86 miRNAs, pan-sensitive and pan-resistant genes with concordant mRNA and protein expression associated with in-vitro drug response to 19 NCCN-recommended breast cancer drugs were selected. Combined with in-vitro proliferation assays using CRISPR-Cas9/RNAi and patient survival analysis, MEK inhibitors PD19830 and BRD-K12244279, pilocarpine, and tremorine were discovered as potential new drug options for treating breast cancer. Multi-omics biomarkers of response to the discovered drugs were identified using human breast cancer cell lines. This study presented an artificial intelligence pipeline of miRNA-based discovery of biomarkers, therapeutic targets, and repositioning drugs that can be applied to many cancer types.

To help achieve the initial goal of providing universal COVID-19 vaccine access to approximately 258 million adults in 62 US jurisdictions, the federal government launched the Federal Retail Pharmacy Program (FRPP) on February 11, 2021. We describe FRPP's collaboration among the federal government, US jurisdictions, federal entity partners, and 21 national chain and independent pharmacy networks to provide large-scale access to COVID-19 vaccines, particularly in communities disproportionately affected by COVID-19 (eg, people aged ≥65 years, people from racial and ethnic minority groups). FRPP initially provided 10 000 vaccination sites for people to access COVID-19 vaccines, which was increased to >35 000 vaccination sites by May 2021 and sustained through January 31, 2022. From February 11, 2021, through January 31, 2022, FRPP vaccination sites received 293 million doses and administered 219 million doses, representing 45% of all COVID-19 immunizations provided nationwide (38% of all first doses, 72% of all booster doses). This unprecedented public-private partnership allowed the federal government to rapidly adapt and scale up an equitable vaccination program to reach adults, later expanding access to vaccine-eligible children, during the COVID-19 pandemic. As the largest federal COVID-19 vaccination program, FRPP exemplifies how public-private partnerships can expand access to immunizations during a public health emergency. Pharmacies can help meet critical national public health goals by serving as convenient access points for sustained health services. Lessons learned from this effort-including the importance of strong coordination and communication, efficient reporting systems and data quality, and increasing access to and demand for vaccine, among others-may help improve future immunization programs and support health system resiliency, emphasizing community-level access and health equity during public health emergencies.

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. In 2020, the COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized hundreds of thousands of specific predictions from more than 50 different academic, industry, and independent research groups. This manuscript systematically evaluates 23 models that regularly submitted forecasts of reported weekly incident COVID-19 mortality counts in the US at the state and national level. One of these models was a multi-model ensemble that combined all available forecasts each week. The performance of individual models showed high variability across time, geospatial units, and forecast horizons. Half of the models evaluated showed better accuracy than a naïve baseline model. In combining the forecasts from all teams, the ensemble showed the best overall probabilistic accuracy of any model. Forecast accuracy degraded as models made predictions farther into the future, with probabilistic accuracy at a 20-week horizon more than 5 times worse than when predicting at a 1-week horizon. This project underscores the role that collaboration and active coordination between governmental public health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks.Competing Interest StatementAV, MC, and APP report grants from Metabiota Inc outside the submitted work.Funding StatementFor teams that reported receiving funding for their work, we report the sources and disclosures below. CMU-TimeSeries: CDC Center of Excellence, gifts from Google and Facebook. CU-select: NSF DMS-2027369 and a gift from the Morris-Singer Foundation. COVIDhub: This work has been supported by the US Centers for Disease Control and Prevention (1U01IP001122) and the National Institutes of General Medical Sciences (R35GM119582). The content is solely the responsibility of the authors and does not necessarily represent the official views of CDC, NIGMS or the National Institutes of Health. Johannes Bracher was supported by the Helmholtz Foundation via the SIMCARD Information&amp; Data Science Pilot Project. Tilmann Gneiting gratefully acknowledges support by the Klaus Tschira Foundation. DDS-NBDS: NSF III-1812699. EPIFORECASTS-ENSEMBLE1: Wellcome Trust (210758/Z/18/Z) GT_CHHS-COVID19: William W. George Endowment, Virginia C. and Joseph C. Mello Endowments, NSF DGE-1650044, NSF MRI 1828187, research cyberinfrastructure resources and services provided by the Partnership for an Advanced Computing Environment (PACE) at Georgia Tech, and the following benefactors at Georgia Tech: Andrea Laliberte, Joseph C. Mello, Richard Rick E. &amp; Charlene Zalesky, and Claudia &amp; Paul Raines GT-DeepCOVID: CDC MInD-Healthcare U01CK000531-Supplement. NSF (Expeditions CCF-1918770, CAREER IIS-2028586, RAPID IIS-2027862, Medium IIS-1955883, NRT DGE-1545362), CDC MInD program, ORNL and funds/computing resources from Georgia Tech and GTRI. IHME: This work was supported by the Bill &amp; Melinda Gates Foundation, as well as funding from the state of Washington and the National Science Foundation (award no. FAIN: 2031096). IowaStateLW-STEM: Iowa State University Plant Sciences Institute Scholars Program, NSF DMS-1916204, NSF CCF-1934884, Laurence H. Baker Center for Bioinformatics and Biological Statistics. JHU_IDD-CovidSP: State of California, US Dept of Health and Human Services, US Dept of Homeland Security, US Office of Foreign Disaster Assistance, Johns Hopkins Health System, Office of the Dean at Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University Modeling and Policy Hub, Centers fo Disease Control and Prevention (5U01CK000538-03), University of Utah Immunology, Inflammation, &amp; Infectious Disease Initiative (26798 Seed Grant). LANL-GrowthRate: LANL LDRD 20200700ER. MOBS-GLEAM_COVID: COVID Supplement CDC-HHS-6U01IP001137-01. NotreDame-mobility and NotreDame-FRED: NSF RAPID DEB 2027718 UA-EpiCovDA: NSF RAPID Grant # 2028401. UCSB-ACTS: NSF RAPID IIS 2029626. UCSD-NEU: Google Faculty Award, DARPA W31P4Q-21-C-0014, COVID Supplement CDC-HHS-6U01IP001137-01. UMass-MechBayes: NIGMS R35GM119582, NSF 1749854. UMich-RidgeTfReg: The University of Michigan Physics Department and the University of Michigan Office of Research.Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:UMass-Amherst IRBAll necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesAll data and code referred to in the manuscript are publicly available. https://github.com/reichlab/covid19-forecast-hub/ https://github.com/reichlab/covidEnsembles https://zoltardata.com/project/44

The 2017-2018 North American influenza season caused more hospitalizations and deaths than any year since the 2009 H1N1 pandemic. The majority of recorded influenza infections were caused by A(H3N2) viruses, with most of the virus’s North American diversity falling into the A2 clade. Within A2, we observe a subclade which we call A2/re that rose to comprise almost 70% of A(H3N2) viruses circulating in North America by early 2018. Unlike most fast-growing clades, however, A2/re contains no amino acid substitutions in the hemagglutinin (HA) segment. Moreover, HI assays did not suggest substantial antigenic differences between A2/re viruses and viruses sampled during the 2016-2017 season. Rather, we observe that the A2/re clade was the result of a reassortment event that occurred in late 2016 or early 2017 and involved the combination of the HA and PB1 segments of an A2 virus with neuraminidase (NA) and other segments a virus from the clade A1b. The success of this clade shows the need for antigenic analysis that targets NA in addition to HA. Our results illustrate the potential for non-HA drivers of viral success and necessitate the need for more thorough tracking of full viral genomes to better understand the dynamics of influenza epidemics.

Next-generation sequencing (NGS) of amplicons is used in a wide variety of contexts. Most NGS amplicon sequencing remains overly expensive and inflexible, with library preparation strategies relying upon the fusion of locus-specific primers to full-length adapter sequences with a single identifying sequence or ligating adapters onto PCR products. In Adapterama I, we presented universal stubs and primers to produce thousands of unique index combinations and a modifiable system for incorporating them into Illumina libraries. Here, we describe multiple ways to use the Adapterama system and other approaches for amplicon sequencing on Illumina instruments. In the variant we use most frequently for large-scale projects, we fuse partial adapter sequences (TruSeq or Nextera) onto the 5’ end of locus-specific PCR primers with variable-length tag sequences between the adapter and locus-specific sequences. These fusion primers can be used combinatorially to amplify samples within a 96-well plate (eight forward primers + 12 reverse primers yield 8 × 12 = 96 combinations), and the resulting amplicons can be pooled. The initial PCR products then serve as template for a second round of PCR with dual-indexed iTru or iNext primers (also used combinatorially) to make full-length libraries. The resulting quadruple-indexed amplicons have diversity at most base positions and can be pooled with any standard Illumina library for sequencing. The number of sequencing reads from the amplicon pools can be adjusted, facilitating deep sequencing when required or reducing sequencing costs per sample to an economically trivial amount when deep coverage is not needed. We demonstrate the utility and versatility of our approaches with results from six projects using different implementations of our protocols. Thus, we show that these methods facilitate amplicon library construction for Illumina instruments at reduced cost with increased flexibility. A simple web page to design fusion primers compatible with iTru primers is available at: http://baddna.uga.edu/tools-taggi.html. A fast and easy to use program to demultiplex amplicon pools with internal indexes is available at: https://github.com/lefeverde/Mr_Demuxy.

Policymakers make decisions about COVID-19 management in the face of considerable uncertainty. We convened multiple modeling teams to evaluate reopening strategies for a mid-sized county in the United States, in a novel process designed to fully express scientific uncertainty while reducing linguistic uncertainty and cognitive biases. For the scenarios considered, the consensus from 17 distinct models was that a second outbreak will occur within 6 months of reopening, unless schools and non-essential workplaces remain closed. Up to half the population could be infected with full workplace reopening; non-essential business closures reduced median cumulative infections by 82%. Intermediate reopening interventions identified no win-win situations; there was a trade-off between public health outcomes and duration of workplace closures. Aggregate results captured twice the uncertainty of individual models, providing a more complete expression of risk for decision-making purposes.

Objectives: The largest mumps outbreak in the United States since 2006 occurred in Arkansas during the 2016-17 school year. An additional dose (third dose) of measles-mumps-rubella vaccine (MMR3) was offered to school children. We evaluated the vaccine effectiveness (VE) of MMR3 compared with two doses of MMR for preventing mumps among school-aged children during the outbreak. Study design: A generalized linear mixed effects model was used to estimate the incremental vaccine effectiveness (VE) of a third dose of MMR compared with two doses of MMR for preventing mumps. Methods: We obtained school enrollment, immunization status and mumps case status from school registries, Arkansas's immunization registry, and Arkansas's mumps surveillance system, respectively. We included students who previously received 2 doses of MMR in schools with ≥1 mumps case after the MMR3 clinic. We used a generalized linear mixed model to estimate VE of MMR3 compared with two doses of MMR. Results: Sixteen schools with 9272 students were included in the analysis. Incremental VE of MMR3 versus a two-dose MMR regimen was 52.7% (95% confidence interval [CI]: -3.6%‒78.4%) overall and in 8 schools with high mumps transmission it was 64.0% (95% CI: 1.2%‒86.9%). MMR3 VE was higher among middle compared with elementary school students (68.5% [95% CI: -30.2%‒92.4%] vs 37.6% [95% CI: -62.5%‒76.1%]); these differences were not statistically significant. Conclusion: Our findings suggest MMR3 provided additional protection from mumps compared with two MMR doses in elementary and middle school settings during a mumps outbreak. © 2023

There is currently no gene expression assay that can assess if premalignant lesions will develop into invasive breast cancer. This study sought to identify biomarkers for selecting patients with a high potential for developing invasive carcinoma in the breast with normal histology, benign lesions, or premalignant lesions. A set of 26-gene mRNA expression profiles were used to identify invasive ductal carcinomas from histologically normal tissue and benign lesions and to select those with a higher potential for future cancer development (ADHC) in the breast associated with atypical ductal hyperplasia (ADH). The expression-defined model achieved an overall accuracy of 94.05% (AUC = 0.96) in classifying invasive ductal carcinomas from histologically normal tissue and benign lesions (n = 185). This gene signature classified cancer development in ADH tissues with an overall accuracy of 100% (n = 8). The mRNA expression patterns of these 26 genes were validated using RT-PCR analyses of independent tissue samples (n = 77) and blood samples (n = 48). The protein expression of PBX2 and RAD52 assessed with immunohistochemistry were prognostic of breast cancer survival outcomes. This signature provided significant prognostic stratification in The Cancer Genome Atlas breast cancer patients (n = 1100), as well as basal-like and luminal A subtypes, and was associated with distinct immune infiltration and activities. The mRNA and protein expression of the 26 genes was associated with sensitivity or resistance to 18 NCCN-recommended drugs for treating breast cancer. Eleven genes had significant proliferative potential in CRISPR-Cas9/RNAi screening. Based on this gene expression signature, the VEGFR inhibitor ZM-306416 was discovered as a new drug for treating breast cancer.

Cryptosporidium canis is a zoonotic species causing cryptosporidiosis in humans in addition to its natural hosts dogs and other fur animals. To understand the genetic basis for host adaptation, we sequenced the genomes of C. canis from dogs, minks, and foxes and conducted a comparative genomics analysis. While the genomes of C. canis have similar gene contents and organisations, they (~41.0 %) and C. felis (39.6 %) have GC content much higher than other Cryptosporidium spp. (24.3-32.9 %) sequenced to date. The high GC content is mostly restricted to subtelomeric regions of the eight chromosomes. Most of these GC-balanced genes encode Cryptosporidium-specific proteins that have intrinsically disordered regions and are involved in host-parasite interactions. Natural selection appears to play a more important role in the evolution of codon usage in GC-balanced C. canis, and most of the GC-balanced genes have undergone positive selection. While the identity in whole genome sequences between the mink- and dog-derived isolates is 99.9 % (9365 SNVs), it is only 96.0 % (362 894 SNVs) between them and the fox-derived isolate. In agreement with this, the fox-derived isolate possesses more subtelomeric genes encoding invasion-related protein families. Therefore, the change in subtelomeric GC content appears to be responsible for the more GC-balanced C. canis genomes, and the fox-derived isolate could represent a new Cryptosporidium species.

Policymakers must make management decisions despite incomplete knowledge and conflicting model projections. Little guidance exists for the rapid, representative, and unbiased collection of policy-relevant scientific input from independent modeling teams. Integrating approaches from decision analysis, expert judgment, and model aggregation, we convened multiple modeling teams to evaluate COVID-19 reopening strategies for a mid-sized United States county early in the pandemic. Projections from seventeen distinct models were inconsistent in magnitude but highly consistent in ranking interventions. The 6-mo-ahead aggregate projections were well in line with observed outbreaks in mid-sized US counties. The aggregate results showed that up to half the population could be infected with full workplace reopening, while workplace restrictions reduced median cumulative infections by 82%. Rankings of interventions were consistent across public health objectives, but there was a strong trade-off between public health outcomes and duration of workplace closures, and no win-win intermediate reopening strategies were identified. Between-model variation was high; the aggregate results thus provide valuable risk quantification for decision making. This approach can be applied to the evaluation of management interventions in any setting where models are used to inform decision making. This case study demonstrated the utility of our approach and was one of several multimodel efforts that laid the groundwork for the COVID-19 Scenario Modeling Hub, which has provided multiple rounds of real-time scenario projections for situational awareness and decision making to the Centers for Disease Control and Prevention since December 2020.

Next-generation sequencing (NGS) of amplicons is used in a wide variety of contexts. In many cases, NGS amplicon sequencing remains overly expensive and inflexible, with library preparation strategies relying upon the fusion of locus-specific primers to full-length adapter sequences with a single identifying sequence or ligating adapters onto PCR products. In Adapterama I, we presented universal stubs and primers to produce thousands of unique index combinations and a modifiable system for incorporating them into Illumina libraries. Here, we describe multiple ways to use the Adapterama system and other approaches for amplicon sequencing on Illumina instruments. In the variant we use most frequently for large-scale projects, we fuse partial adapter sequences (TruSeq or Nextera) onto the 5' end of locus-specific PCR primers with variable-length tag sequences between the adapter and locus-specific sequences. These fusion primers can be used combinatorially to amplify samples within a 96-well plate (8 forward primers + 12 reverse primers yield 8 × 12 = 96 combinations), and the resulting amplicons can be pooled. The initial PCR products then serve as template for a second round of PCR with dual-indexed iTru or iNext primers (also used combinatorially) to make full-length libraries. The resulting quadruple-indexed amplicons have diversity at most base positions and can be pooled with any standard Illumina library for sequencing. The number of sequencing reads from the amplicon pools can be adjusted, facilitating deep sequencing when required or reducing sequencing costs per sample to an economically trivial amount when deep coverage is not needed. We demonstrate the utility and versatility of our approaches with results from six projects using different implementations of our protocols. Thus, we show that these methods facilitate amplicon library construction for Illumina instruments at reduced cost with increased flexibility. A simple web page to design fusion primers compatible with iTru primers is available at: http://baddna.uga.edu/tools-taggi.html. A fast and easy to use program to demultiplex amplicon pools with internal indexes is available at: https://github.com/lefeverde/Mr_Demuxy.

Simple Summary: This study identified a set of 73 microRNAs (miRNAs) that can accurately detect lung cancer tumors from normal lung tissues. Based on the consistent expression patterns associated with patient survival outcomes and in tumors vs. normal lung tissues, 10 miRNAs were considered to be putatively tumor suppressive and 4 miRNAs were deemed as oncogenic in lung cancer. From the list of genes that were targeted by the 73 diagnostic miRNAs, DGKE and WDR47 had significant associations with responses to both systemic therapies and radiotherapy in lung cancer. Based on our identified miRNA-regulated network, we discovered three drugs—BX-912, daunorubicin, and midostaurin—that can be repositioned to treat lung cancer, which was not known before. The majority of lung cancer patients are diagnosed with metastatic disease. This study identified a set of 73 microRNAs (miRNAs) that classified lung cancer tumors from normal lung tissues with an overall accuracy of 96.3% in the training patient cohort (n = 109) and 91.7% in unsupervised classification and 92.3% in supervised classification in the validation set (n = 375). Based on association with patient survival (n = 1016), 10 miRNAs were identified as potential tumor suppressors (hsa-miR-144, hsa-miR-195, hsa-miR-223, hsa-miR-30a, hsa-miR-30b, hsa-miR-30d, hsa-miR-335, hsa-miR-363, hsa-miR-451, and hsa-miR-99a), and 4 were identified as potential oncogenes (hsa-miR-21, hsa-miR-31, hsa-miR-411, and hsa-miR-494) in lung cancer. Experimentally confirmed target genes were identified for the 73 diagnostic miRNAs, from which proliferation genes were selected from CRISPR-Cas9/RNA interference (RNAi) screening assays. Pansensitive and panresistant genes to 21 NCCN-recommended drugs with concordant mRNA and protein expression were identified. DGKE and WDR47 were found with significant associations with responses to both systemic therapies and radiotherapy in lung cancer. Based on our identified miRNA-regulated molecular machinery, an inhibitor of PDK1/Akt BX-912, an anthracycline antibiotic daunorubicin, and a multi-targeted protein kinase inhibitor midostaurin were discovered as potential repositioning drugs for treating lung cancer. These findings have implications for improving lung cancer diagnosis, optimizing treatment selection, and discovering new drug options for better patient outcomes.

BACKGROUND: Data are limited on influenza testing among adults with acute respiratory illness (ARI)-associated hospitalizations. We identified factors associated with influenza testing in adult ARI-associated hospitalizations across the 2016-2017 through 2019-2020 influenza seasons. METHODS: Using data from 4 health systems in the United States, we identified hospitalizations that had an ARI discharge diagnosis or respiratory virus test. A hospitalization with influenza testing was based on testing performed within 14 days before through 72 hours after admission. We used random forest analysis to identify patient characteristics and influenza activity indicators that were most important in terms of their relationship to influenza testing. RESULTS: Across 4 seasons, testing rates ranged from 14.8%-19.4% at 3 pooled sites and 60.1%-78.5% at a fourth site with different testing practices. Discharge diagnoses of pneumonia or infectious disease of noninfluenza etiology, presence of ARI signs/symptoms, hospital admission month, and influenza-like illness activity level were consistently among the variables with the greatest relative importance. CONCLUSIONS: Select ARI diagnoses and indicators of influenza activity were the most important factors associated with influenza testing among ARI-associated hospitalizations. Improved understanding of which patients are tested may enhance influenza burden estimates and allow for more timely clinical management of influenza-associated hospitalizations.

We conducted environmental surveillance to detect avian influenza viruses circulating at live poultry markets (LPMs) and poultry farms in Guangxi Autonomous Region, China, where near the China-Vietnam border. From November through April 2017–2018 and 2018–2019, we collected environmental samples from 14 LPMs, 4 poultry farm, and 5 households with backyard poultry in two counties of Guangxi and tested for avian influenza A, H5, H7, and H9 by real-time reverse transcription-polymerase chain reaction (rRT-PCR). In addition, we conducted four cross-sectional questionnaire surveys among stall owners on biosecurity practices in LPMs of two study sites. Among 16,713 environmental specimens collected and tested, the median weekly positive rate for avian influenza A was 53.6% (range = 33.5% − 66.0%), including 25.2% for H9, 4.9% for H5, and 21.2% for other avian influenza viruses A subtypes, whereas a total of two H7 positive samples were detected. Among the 189 LPM stalls investigated, most stall owners (73.0%) sold chickens and ducks. Therefore, continued surveillance of the avian influenza virus is necessary for detecting and responding to emerging trends in avian influenza virus epidemiology. © 2023

We conducted environmental surveillance to detect avian influenza viruses circulating at live poultry markets (LPMs) and poultry farms in Guangxi Autonomous Region, China, where near the China-Vietnam border. From November through April 20172018 and 20182019, we collected environmental samples from 14 LPMs, 4 poultry farm, and 5 households with backyard poultry in two counties of Guangxi and tested for avian influenza A, H5, H7, and H9 by real-time reverse transcription-polymerase chain reaction (rRT-PCR). In addition, we conducted four cross-sectional questionnaire surveys among stall owners on biosecurity practices in LPMs of two study sites. Among 16,713 environmental specimens collected and tested, the median weekly positive rate for avian influenza A was 53.6% (range = 33.5% 66.0%), including 25.2% for H9, 4.9% for H5, and 21.2% for other avian influenza viruses A subtypes, whereas a total of two H7 positive samples were detected. Among the 189 LPM stalls investigated, most stall owners (73.0%) sold chickens and ducks. Therefore, continued surveillance of the avian influenza virus is necessary for detecting and responding to emerging trends in avian influenza virus epidemiology. 2023

The parasite Cryptosporidium hominis is a leading cause of the diarrheal disease cryptosporidiosis, whose incidence in the United States has increased since 2005. Here, we show that the newly emerged and hyper-transmissible subtype IfA12G1R5 is now dominant in the United States. In a comparative analysis of 127 newly sequenced and 95 published C. hominis genomes, IfA12G1R5 isolates from the United States place into three of the 14 clusters (Pop6, Pop13, and Pop14), indicating that this subtype has multiple ancestral origins. Pop6 (IfA12G1R5a) has an East Africa origin and has recombined with autochthonous subtypes after its arrival. Pop13 (IfA12G1R5b) is imported from Europe, where it has recombined with the prevalent local subtype, whereas Pop14 (IfA12G1R5c) is a progeny of secondary recombination between Pop6 and Pop13. Selective sweeps in invasion-associated genes have accompanied the emergence of the dominant Pop14. These observations offer insights into the emergence and evolution of hyper-transmissible pathogens.

AIM: To examine changes in racial and ethnic disparities in glucose-lowering drugs (GLD) use and glycated haemoglobin A1c in US adults with diabetes from 2005 to 2018. METHODS: We conducted pooled cross-sectional analysis using data from the 2005-2018 Medical Expenditure Panel Surveys, and the 2005-2018 National Health and Nutrition Examination Survey. Individuals ≥18 years with diabetes were included. Racial and ethnic disparities were measured in (a) newer non-insulin GLD use; (b) insulin analogue use; (c) non-insulin GLDs adherence; (d) insulin adherence; and (e) glucose management, along with (f) the proportion of the disparities explained by potential contributing factors. RESULTS: From 2005 to 2018, racial and ethnic disparities persisted in newer GLD use, non-insulin GLDs adherence, insulin analogue use and glucose management. In 2018, compared with non-Hispanic white adults, non-Hispanic black, Hispanic and other race/ethnicity groups had lower rates of using newer GLDs (adjusted risk ratio: 0.44, 0.52, 0.64, respectively; p < .05 for all) and insulin analogues (adjusted risk ratio: 0.93, 0.89, 0.95, respectively; p < .05 for all except other groups), lower non-insulin GLD adherence (proportion of days covered: -4.5%, -5.6%, -4.3%, respectively; p < .05 for all), higher glycated haemoglobin A1c (0.29%, 0.32%, 0.02%, respectively; p < .05 for all except other group), and similar insulin adherences. Socioeconomic and health status were the main contributors to these disparities. CONCLUSIONS: Our findings provide evidence of racial and ethnic disparities in newer GLD use and quality of care in glucose management. Our study results can inform decision-makers of the status of racial and ethnic disparities and identify ways to reduce these disparities.

OBJECTIVES: This study aimed to estimate the cost-effectiveness of the use of recombinant zoster vaccine (RZV) (Shingrix), which protects against herpes zoster (HZ), among immunocompromised adults aged 19 to 49 years, as a contribution to deliberations of the Advisory Committee on Immunization Practices. METHODS: Hematopoietic cell transplant (HCT) recipients experience a high incidence of HZ, and the efficacy of RZV in preventing HZ has been studied in clinical trials. The cost-effectiveness model calculated incremental cost-effectiveness ratios that compared vaccination with RZV with a no vaccination strategy among adults aged 19 to 49 years. Costs and outcomes were calculated until age 50 years using the healthcare sector perspective and summarized as cost per quality-adjusted life-year (QALY) gained. The base case represents HCT recipients, with scenario analyses representing persons with other immunocompromising conditions, including hematologic malignancies, human immunodeficiency virus, and autoimmune and inflammatory conditions. Uncertainty was investigated using univariate, multivariate, and probabilistic sensitivity analyses. RESULTS: Base-case results indicated vaccination with RZV would avert approximately 35% of HZ episodes and complications, while saving approximately 11% of net costs. Compared with no vaccination, vaccination of HCT recipients with RZV generated cost-savings (ie, lower costs and improved health) in the base case and in 81% of simulations in the probabilistic analysis. In scenario analyses, vaccination cost US dollar ($) 9500/QALY among patients with hematologic malignancies, $79000/QALY among persons living with human immunodeficiency virus, and $208000/QALY among persons with selected autoimmune and inflammatory conditions. CONCLUSIONS: Generally favorable economic estimates supported recommendations for vaccination of immunocompromised adults with RZV to prevent episodes of HZ and related complications.

Whether lowering the hemoglobin A1c to <6.0% in patients with type 2 diabetes can reduce the risk of cardiovascular disease (CVD) remains under debate. The ACCORDION and the VADT studies both found reductions in the primary CVD composite associated with intensive glycemic control, though the difference is not statistically significant. However, the lack of significance is often overinterpreted as non-effective: a p-value >0.05 only implies that the study "failed to reject" the null hypothesis (i.e., lowering the A1c level to <6.0% results in no CVD benefit), which is different from concluding the null hypothesis being true. In this study, we used Bayesian analysis to reanalyze results from the ACCORDION and VADT-15 trials. Our results suggest achieving an A1c goal of <6.0% as compared to moderate control could result in a moderate risk reduction in MACE.

Although some adults infected with influenza 2009 A(H1N1)pdm09 viruses mounted high hemagglutination inhibition (HAI) antibody response, they still suffered from severe disease, or even death. Here, we analyzed antibody profiles in patients (n = 31, 17-65 years) admitted to intensive care units (ICUs) with lung failure and invasive mechanical ventilation use due to infection with A(H1N1)pdm09 viruses during 2009-2011. We performed a comprehensive analysis of the quality and quantity of antibody responses using HAI, virus neutralization, biolayer interferometry, enzyme-linked-lectin and enzyme-linked immunosorbent assays. At time of the ICU admission, 45% (14/31) of the patients had HAI antibody titers ≥ 80 in the first serum (S1), most (13/14) exhibited narrowly-focused HAI and/or anti-HA-head binding antibodies targeting single epitopes in or around the receptor binding site. In contrast, 42% (13/31) of the patients with HAI titers ≤ 10 in S1 had non-neutralizing anti-HA-stem antibodies against A(H1N1)pdm09 viruses. Only 19% (6/31) of the patients showed HA-specific IgG1-dominant antibody responses. Three of 5 fatal patients possessed highly focused cross-type HAI antibodies targeting the (K130 + Q223)-epitopes with extremely low avidity. Our findings suggest that narrowly-focused low-quality antibody responses targeting specific HA-epitopes may have contributed to severe infection of the lower respiratory tract.

Essential agricultural workers work under occupational conditions that may increase the risk of SARS-CoV-2 exposure and transmission. Data from an agricultural worker cohort in Guatemala, and anti-SARS-CoV-2 nucleocapsid IgG (anti-N IgG) testing were used to estimate past infections and analyze risk factors associated with seropositivity at enrollment and association with SARS-CoV-2 infection. The stability of neutralizing antibody (NAb) responses were assessed in a subset of participants. The adjusted relative risk (aRR) for seroprevalence at enrollment was estimated accounting for correlations within worksites. At enrollment, 616 (46.2%) of 1334 (93.2%) participants had anti-N IgG results indicating prior SARS-CoV-2 infection. A cough ≤ 10 days prior to enrollment (aRR = 1.28, 95% CI: 1.13-1.46) and working as a packer (aRR = 2.00, 95% CI: 1.67-2.38) or packing manager within the plants (aRR = 1.82, 95% CI: 1.36-2.43) were associated with increased risk of seropositivity. COVID-19 incidence density among seronegative workers was 2.3/100 Person-Years (P-Y), higher than seropositive workers (0.4/100 P-Y). Most workers with follow-up NAb testing (65/77, 84%) exhibited a 95% average decrease in NAb titers in &lt;6 months. While participants seropositive at baseline were less likely to experience a symptomatic SARS-CoV-2 infection during follow-up, NAb titers rapidly waned, underscoring the need for multipronged COVID-19 prevention strategies in the workplace, including vaccination.