Merck Institute for Science Education

Abstract The standard model (SM) in particle physics is a well-established and extensively tested theory, formulated using advanced mathematical frameworks such as gauge theory. This study presents a periodic table of SM particles as a simplified tool, without relying on such advanced mathematics. Each SM particle is assigned a number in the table, analogous to an atom in the periodic table of elements. The decay modes of baryons and mesons were analyzed using particle inversion numbers (P-INs), defined as the binary representation of each particle's decimal number. The analysis revealed a “multiple-of-four” rule for the P-INs of baryons and mesons decay modes, enabling their classification into two groups: multiples of four and non-multiples of four. For instance, a neutron has a P-IN of 16 (a multiple of four), whereas a proton has a P-IN of 14 (not a multiple of four). The P-INs of SM particles indicate that reactions across the three generations follow analogous P-IN patterns. These numerical values introduce a new perspective based on binary numbers: the even P-IN values (0, 4, 6) and the odd codon inversion numbers (C-INs) in the genetic code (1, 3, 5) suggest a habitat segregation relationship between elementary particles and proteins, reflected in the even and odd values of their inversion numbers.

BackgroundIn KEYNOTE-522 (NCT03036488), neoadjuvant pembrolizumab plus chemotherapy and then adjuvant pembrolizumab significantly improved pathological complete response and event-free survival vs neoadjuvant chemotherapy in early-stage triple-negative breast cancer (TNBC). We report patient-reported outcomes (PROs) from KEYNOTE-522.MethodsPatients were randomized 2:1 to neoadjuvant pembrolizumab 200 mg or placebo every 3 weeks, plus 4 cycles of paclitaxel plus carboplatin and then 4 cycles of doxorubicin (or epirubicin) plus cyclophosphamide. After surgery, patients received adjuvant pembrolizumab or placebo for up to 9 cycles. European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire–Core 30 (EORTC QLQ-C30) and EORTC Breast Cancer-Specific Quality of Life Questionnaire (EORTC QLQ-BR23) were prespecified secondary objectives. Between-group differences in least squares (LS) mean change from baseline (day 1 of cycle 1 in both neoadjuvant and adjuvant phases) to the prespecified latest time point with at least 60% completion and at least 80% compliance were assessed using a longitudinal model (no alpha error assigned).ResultsWeek 21 (neoadjuvant phase) and week 24 (adjuvant phase) were the latest time points at which completion/compliance rates were ≥60%/80%. In the neoadjuvant phase, between-group differences (pembrolizumab plus chemotherapy [n = 762] vs placebo plus chemotherapy [n = 383]) in LS mean change from baseline to week 21 in QLQ-C30 global health status/quality of life (GHS/QoL), emotional functioning, and physical functioning were −1.04 (95% confidence interval = −3.46 to 1.38), −0.69 (95% CI = −3.13 to 1.75), and −2.85 (95% CI = −5.11 to −0.60), respectively. In the adjuvant phase, between-group differences (pembrolizumab [n = 539] vs placebo [n = 308]) in LS mean change from baseline to week 24 were −0.41 (95% CI = −2.60 to 1.77), −0.60 (95% CI = −2.99 to 1.79), and −1.57 (95% CI = −3.36 to 0.21).ConclusionsNo substantial differences in PRO assessments were observed between neoadjuvant pembrolizumab plus chemotherapy followed by adjuvant pembrolizumab vs neoadjuvant placebo plus chemotherapy in early-stage TNBC.Trial registrationClinicalTrials.gov, NCT03036488.

Abstract Background New Jersey plans to reduce 75% of new HIV infections and promote access to testing and linkage-to-care (LTC) to end the HIV epidemic by 2025. In the US, CDC 2020 hepatitis surveillance report indicated cases of hepatitis C in 2020 corresponded to a 124% increase from 2013. Globally, if the HBV effort remains unchanged, the annual deaths from HBV are projected to increase by 39% from 2015 to 2030. We implemented an electronic medical record (EMR) based screening algorithm to scale up HBV, HCV, and HIV screening and provide LTC. Methods In March 2018, the EMR was modified at Cooperman Barnabas Medical Center in the Emergency Department (ED) to start automated screening, we expanded the screening criteria to boost identifying the undiagnosed. Subsequently, the program expanded to Somerset Medical Center and Rahway Hospital. Patient Navigators receive a real-time alert of positive results to contact patients and arrange LTC, the multidisciplinary team offers evaluation and treatment.Figure 1.Expanding Automated Screening Program Results We found HIV prevalence in CBMC is 1.5%, close to 5 times the NJ statewide 397.2 per 100,000 population. HBV infection rates varied in three hospitals, representative of the diverse population in their service areas. The HBV patients we confirmed came from more than 170 countries with different insurance statuses, the majority are immigrants from endemic countries or with high-risk behaviors identified. From Aug 2022, new HbsAg + cases reflex to HDVAb test, where 5% resulted HDVAb+ and no HDVRNA+. HCV prevalence rates are more consistent among the three sites, however, the percentages of the birth cohort (1945-1965) are varied. LTC rates are higher in HBV patients than HCV, thus far, 41 patients were cured of HCV from our team.Figure 2.Total Numbers of HBV, HCV & HIV Tested, Prevalence & LTC Conclusion EMR automated screening significantly scales up the diagnosis of HBV, HCV and HIV, as well as identifying HIV at-risk patients to receive comprehensive preventative services. HBV, HCV and HIV share similar risks, LTC is crucial to treat current infections and is beneficial to prevent transmission and potential exposure. In summary, automated screening and LTC work robustly toward elimination. Disclosures All Authors: No reported disclosures

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Multivariate curve resolution-alternating least squares (MCR-ALS) applied to hyperspectral Raman imaging is extensively used to spatially and spectrally resolve the individual, pure chemical species within complex, heterogeneous samples. A critical aspect of performing MCR-ALS with hyperspectral Raman imaging is the selection of the number of chemical components within the experimental data. Several methods have previously been proposed to determine the number of chemical components, but it remains a challenging task that if done incorrectly, can lead to the loss of chemical information. In this work, we show that the choice of 'optimal' number of factors in the MCR-ALS model may vary depending on the relative contribution of the targeted species to the overall spectral intensity. In a data set consisting of 27 hyperspectral Raman images of TiO2 polymorphs, it was observed that the more dominant species were best resolved with a parsimonious model. However, species with intensities near the noise level often needed more factors to be resolved than was predicted by standard methods. Based on the observations in this data set, we propose a new method that employs approximate reference spectra for determining optimal model complexity for identifying minor constituents with MCR-ALS.

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