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Enzymes in secondary pharmacology screening panels: is there room for improvement?
Single-chip silicon photonic engine for analog optical and microwave signals processing
Ground subsidence evolution and groundwater variation in the middle route of south to north water diversion project
Shaping secondary pharmacology panels of the future: evolving target selection criteria for safety panels
Exploring the potential of the COI gene marker for DNA barcoding of planktonic foraminifera
Abstract Metabarcoding is a cornerstone of modern ecology, but its accuracy is dependent on the chosen gene marker. While the small subunit ribosomal DNA (SSU) is a powerful tool to describe protist diversity, its reliability in retrieving the composition of communities is less obvious. It is particularly challenging to obtain quantitative estimates of abundance in planktonic foraminifera, where the variability of the SSU gene copy number can span three orders of magnitude. As an alternative, we explored the potential of the mitochondrial cytochrome c oxidase subunit I (COI) marker. We developed a reference barcode library of 130 sequences of a 1200 bp long COI fragment belonging to 26 morphospecies of foraminifera and performed 201 single-cell qPCR quantifications to evaluate the relationship between the number of COI copies, and the size of individual foraminifera. We found that the COI evolves between 25 and 1000 times slower than the SSU and therefore has a poor taxonomic resolution. However, we observed a significant relationship between COI copy number and foraminifera size. These results suggest that SSU and COI can play complementary roles: the SSU is well-suited for capturing taxonomic diversity, while the COI is useful to retrieve crude information on the community composition.
Investigation of cold formed steel angle compression through high throughput design FEA and machine learning
Analysis of China-to-West pharmaceutical licensing deals in 2024
Trends in the drug target landscape for autoimmune diseases
Active monitoring of DCIS shows promise in short‐term study
Livebirth rates significantly lower among women diagnosed with cancer
From success to sustained action: Tobacco control must remain a priority
Beyond fluorodeoxyglucose: Molecular imaging of cancer in precision medicine
Abstract Cancer molecular imaging is the noninvasive visualization of a process unique to or altered in neoplasia, such as proliferation, glucose metabolism, and receptor expression, which is relevant to patient management. Several molecular imaging modalities are now available, including magnetic resonance, optical, and nuclear imaging. Nuclear imaging, particularly using fluorine‐18–fluorodeoxyglucose positron emission tomography, is widely used in the staging and response assessment of multiple cancer types. However, at this writing, new nuclear medicine probes, especially positron emission tomography tracers, are increasingly used or are being investigated for cancer evaluation. This review focuses on these probes, their biologic targets, and the applications or potential applications for their use in the assessment of various neoplasms, including both probes available for commercial use—such as somatostatin receptor ligands in neuroendocrine tumors, prostate‐specific membrane antigen ligands in prostate cancer, norepinephrine analogs in neural crest tumors like neuroblastoma, and estrogen analogs in breast cancer—and others in clinical development, such as fibroblast‐activating protein inhibitors, C‐X‐C chemokine receptor type 4 ligands, and monoclonal antibodies targeting receptor tyrosine kinases, CD4‐positive or CD8‐positive tumor‐infiltrating lymphocytes, tumor‐associated macrophages, and cancer stem cell biomarkers. These developments represent a major step toward the integration of molecular imaging as a powerful tool in precision medicine, with an expectedly significant impact on patient management and outcome.
Life science ecosystems in Asia: biomedical innovation trends over the past decade
Averted lung cancer deaths due to reductions in cigarette smoking in the United States, 1970–2022
Abstract Lung cancer mortality rates in the United States have declined steeply in recent decades, largely because of substantial reductions in smoking prevalence, as approximately 85% of lung cancer deaths are attributable to cigarette smoking. In this study, the authors estimate the number of averted lung cancer deaths and corresponding person‐years of life gained during 1970–2022 as a measure of progress in cancer prevention through tobacco control. By using the 1970–2022 National Center for Health Statistics mortality data (with national coverage), the authors calculated the expected number of deaths for each year, age, sex, race, and age group based on the expected lung cancer death rate multiplied by the population at risk in that group. The number of averted lung cancer deaths were calculated by subtracting the observed number of deaths from the expected number in each group. Person‐years of life gained were estimated as a measure of avoided premature mortality based on the average additional years a person would have lived if they had not died from lung cancer. The authors estimated that 3,856,240 lung cancer deaths (2,246,610 in men, 1,609,630 in women) were averted, and 76,275,550 person‐years of life (40,277,690 in men, 35,997,860 in women) were gained during 1970–2022, with an average of 19.8 person‐years of life gained (17.9 in men, 22.4 in women) per averted death. The number of averted lung cancer deaths accounted for 51.4% of the estimated declines in overall cancer deaths and was substantially greater in men (60.1%) than in women (42.7%). By race, this proportion was 53.6% in the White population (62.8% in men, 44.6% in women) and 40.0% in the Black population (44.4% in men, 34.7% in women). The substantial estimated numbers of averted lung cancer deaths and person‐years of life gained highlight the remarkable effect of progress against smoking on reducing premature mortality from lung cancer.
Treatment adaptation based on response to induction chemotherapy in nasopharyngeal carcinoma: An evolving landscape
Defeating lethal cancer: Interrupting the ecologic and evolutionary basis of death from malignancy
Abstract Despite the advances in cancer prevention, early detection, and treatments, all of which have led to improved cancer survival, globally, there is an increased incidence in cancer‐related deaths. Although each patient and each tumor is wholly unique, the tipping point to incurable disease is common across all patients: the dual capacity for cancers to metastasize and resist systemic treatment. The discovery of genetic mutations and epigenetic variation that emerges during cancer progression highlights that evolutionary and ecology principles can be used to understand how cancer evolves to a lethal phenotype. By applying such an eco‐evolutionary framework, the authors reinterpret our understanding of the metastatic process as one of an ecologic invasion and define the eco‐evolutionary paths of evolving therapy resistance. With this understanding, the authors draw from successful strategies optimized in evolutionary ecology to define strategic interventions with the goal of altering the evolutionary trajectory of lethal cancer. Ultimately, studying, understanding, and treating cancer using evolutionary ecology principles provides an opportunity to improve the lives of patients with cancer.
Reduced‐volume radiotherapy versus conventional‐volume radiotherapy after induction chemotherapy in nasopharyngeal carcinoma: An open‐label, noninferiority, multicenter, randomized phase 3 trial
Abstract Background Nearly 90% locoregionally advanced nasopharyngeal carcinoma (LANPC) responds to induction chemotherapy (IC) with significant tumor volume shrinkage. Radiotherapy always follows IC, and reduced volume has been proposed. However, the efficacy and safety of reduced‐volume radiotherapy is uncertain. Methods In this multi‐center, noninferiority, randomized, controlled trial, patients with LANPC who completed IC were randomly assigned (1:1) to receive reduced‐volume radiotherapy based on post‐IC tumor volume (Post‐IC group) or conventional volume radiotherapy based on pre‐IC tumor volume (Pre‐IC group). The primary endpoint was locoregional relapse‐free survival, with a noninferiority margin of 8%. Secondary endpoints comprised adverse events, and quality of life (QoL). Results Between August 7, 2020, and May 27, 2022, 445 patients were randomly assigned to Post‐IC ( n = 225) or Pre‐IC ( n = 220) groups. The average volume receiving radical dose was 66.6 cm 3 in Post‐IC group versus 80.9 cm 3 . After a median follow‐up of 40.4 months, the 3‐year locoregional relapse‐free survival was 91.5% in the Post‐IC group versus 91.2%, with a difference of 0.3% (95% confidence interval −4.9% to 5.5%). The incidence of grade 3‐4 radiation‐related toxicity was lower in the Post‐IC group including: acute mucositis (19.8% vs 34.1%), late otitis media (9.5% vs 20.9%) and late dry month (3.6% vs 9.5%). The Post‐IC group had better QoL for global health status, physical functioning, emotional functioning, dry mouth and sticky saliva. Conclusions In this trial, reduced‐volume radiotherapy was noninferior to conventional volume radiotherapy in locoregional relapse‐free survival, and was associated with lower toxicities and improved QoL. (ClinicalTrials.gov identifier NCT04384627).
Novel clinical trial designs emerging from the molecular reclassification of cancer
Abstract Next‐generation sequencing has revealed the disruptive reality that advanced/metastatic cancers have complex and individually distinct genomic landscapes, necessitating a rethinking of treatment strategies and clinical trial designs. Indeed, the molecular reclassification of cancer suggests that it is the molecular underpinnings of the disease, rather than the tissue of origin, that mostly drives outcomes. Consequently, oncology clinical trials have evolved from standard phase 1, 2, and 3 tissue‐specific studies; to tissue‐specific, biomarker‐driven trials; to tissue‐agnostic trials untethered from histology (all drug‐centered designs ); and, ultimately, to patient‐centered , N‐of‐1 precision medicine studies in which each patient receives a personalized, biomarker‐matched therapy/combination of drugs. Innovative technologies beyond genomics, including those that address transcriptomics, immunomics, proteomics, functional impact, epigenetic changes, and metabolomics, are enabling further refinement and customization of therapy. Decentralized studies have the potential to improve access to trials and precision medicine approaches for underserved minorities. Evaluation of real‐world data, assessment of patient‐reported outcomes, use of registry protocols, interrogation of exceptional responders, and exploitation of synthetic arms have all contributed to personalized therapeutic approaches. With greater than 1 × 10 12 potential patterns of genomic alterations and greater than 4.5 million possible three‐drug combinations, the deployment of artificial intelligence/machine learning may be necessary for the optimization of individual therapy and, in the near future, also may permit the discovery of new treatments in real time.