Immunotherapy toxicity: identification and management

The widespread adoption of immunotherapy has revolutionized the treatment of various cancer types, including metastatic triple-negative breast cancer (TNBC), which has long been associated with poor prognostic outcomes. In particular, immune checkpoint inhibitors (ICIs) that target and inhibit programmed cell death-1 (PD-1) and programmed cell death ligand-1 (PD-L1), have shown promising results in the treatment of patients with metastatic TNBC. However, while manipulating the immune system to induce antitumor response, ICIs can also lead to a unique set of immune-related adverse events (IRAEs), which differ from standard chemotherapy toxicities due to their immune-based origin. These toxicities require highly specific management, including guidance from multidisciplinary specialists. The primary treatment strategy against IRAEs is systemic corticosteroid use, but additional treatment approaches may also involve supportive care, additional immunosuppression, and concurrent treatment delay or discontinuation. Given the rising prevalence of ICI therapy, it is essential to educate clinicians on the presentation and management of these potentially life-threatening events so that they are identified early and treated appropriately. Using data from recent clinical trials, this review will focus on known IRAEs, particularly those seen in patients with breast cancer, and will summarize their prevalence, severity, and outcomes. We will discuss optimal strategies for early recognition and management, as well as approaches toward cautious retreatment following resolution of IRAEs.

A practical water–energy–climate solution for sustainable and resilient coastal cities: smart use of seawater in municipal services

Municipal services for buildings in developed (sub)tropical coastal cities contributed 18% of greenhouse gases (GHGs) in 2020. One mitigatory solution is the direct use of seawater for district cooling and toilet flushing, which has been applied in Hong Kong on various scales and achieved 30% water and energy savings. However, no systematic evaluation and strategy for this solution are available. Herein, we develop a high-resolution quantitative scheme to elaborate the co-benefits and optimal strategies for expanding this use of seawater. We find that in Hong Kong, Jeddah, and Miami, using local seawater at the city-scale would achieve life-cycle GHG mitigation (42%–56%), energy savings (45%–49%), and freshwater savings (11%–43%). High-resolution analysis reveals that population density and district marginal performance are essential to optimize the efficiency of seawater use. Our scheme confirms the utility of seawater for municipal services and is an effective tool for innovative municipal-service enhancement.

Optimized splitting of mixed-species RNA sequencing data

Gene expression studies using xenograft transplants or co-culture systems, usually with mixed human and mouse cells, have proven to be valuable to uncover cellular dynamics during development or in disease models. However, the mRNA sequence similarities among species presents a challenge for accurate transcript quantification. To identify optimal strategies for analyzing mixed-species RNA sequencing data, we evaluate both alignment-dependent and alignment-independent methods. Alignment of reads to a pooled reference index is effective, particularly if optimal alignments are used to classify sequencing reads by species, which are re-aligned with individual genomes, generating [Formula: see text] accuracy across a range of species ratios. Alignment-independent methods, such as convolutional neural networks, which extract the conserved patterns of sequences from two species, classify RNA sequencing reads with over 85% accuracy. Importantly, both methods perform well with different ratios of human and mouse reads. While non-alignment strategies successfully partitioned reads by species, a more traditional approach of mixed-genome alignment followed by optimized separation of reads proved to be the more successful with lower error rates.

Optimal strategies to protect a sub-population at risk due to an established epidemic

Epidemics can particularly threaten certain sub-populations. For example, for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the elderly are often preferentially protected. For diseases of plants and animals, certain sub-populations can drive mitigation because they are intrinsically more valuable for ecological, economic, socio-cultural or political reasons. Here, we use optimal control theory to identify strategies to optimally protect a ‘high-value’ sub-population when there is a limited budget and epidemiological uncertainty. We use protection of the Redwood National Park in California in the face of the large ongoing state-wide epidemic of sudden oak death (caused by Phytophthora ramorum ) as a case study. We concentrate on whether control should be focused entirely within the National Park itself, or whether treatment of the growing epidemic in the surrounding ‘buffer region’ can instead be more profitable. We find that, depending on rates of infection and the size of the ongoing epidemic, focusing control on the high-value region is often optimal. However, priority should sometimes switch from the buffer region to the high-value region only as the local outbreak grows. We characterize how the timing of any switch depends on epidemiological and logistic parameters, and test robustness to systematic misspecification of these factors due to imperfect prior knowledge.

The rich-to-poor vaccine donation game: When will self-interested countries donate their surplus vaccines during pandemics?

When will self-interested vaccine-rich countries voluntarily donate their surplus vaccines to vaccine-poor countries during a pandemic? We develop a game-theoretic approach to address this question. We identify vaccine-rich countries' optimal surplus donation strategies, and then examine whether these strategies are stable (Nash equilibrium or self-enforcing international agreement). We identify parameter ranges in which full or partial surplus stock donations are optimal for the donor countries. Within a more restrictive parameter region, these optimal strategies are also stable. This implies that, under certain conditions (notably a total amount of surplus vaccines that is sufficiently large), simple coordination can lead to significant donations by strictly self-interested vaccine-rich countries. On the other hand, if the total amount that the countries can donate is small, we expect no contribution from self-interested countries. The results of this analysis provide guidance to policy makers in identifying the circumstances in which coordination efforts are likely to be effective.