Catalytic Dual-Mode Immunotherapy: Anisotropic AuPt Heterostructure Decorated with Starry Pt Nanoclusters for Robust Cancer Photometalloimmunotherapy.

To overcome current limitations in photoimmunotherapy, such as insufficient tumor antigen generation and a subdued immune response, a novel photo-/metallo dual-mode immunotherapeutic agent (PMIA) is introduced for potent near-infrared (NIR) light-triggered cancer therapy. PMIA features a dumbbell-like AuPt heterostructure decorated with starry Pt nanoclusters, meticulously engineered for enhancing plasmonic catalysis through multi-dimensional regulation of Pt growth on Au nanorods. Under NIR laser exposure, end-tipped Pt nanoclusters induce efficient electron-hole spatial separation along the longitudinal axis, resulting in radial and axial electron distribution polarization, conferring unique anisotropic properties to PMIA. Additionally, starry Pt nanoclusters on the sides of Au nanorods augment the local electron enrichment field. Validated through finite-difference time-domain analysis and Raman scattering, this configuration fosters local electron enrichment, facilitating robust reactive oxygen species generation for potent photoimmunotherapy. Moreover, Pt nanoclusters facilitate Pt2+ ion release, instigating intranuclear DNA damage and inducing synergistic immunogenic cell death (ICD) for metalloimmunotherapy. Consequently, PMIA elicits abundant danger-associated molecular patterns, promotes T cell infiltration, and triggers systemic immune responses, effectively treating primary and distant tumors, inhibiting metastasis in vivo. This study unveils a pioneering dual-mode ICD amplification strategy driven by NIR light, synergistically integrating photoimmunotherapy and metalloimmunotherapy, culminating in potent cancer photometalloimmunotherapy.

An Immunomodulatory Zinc-Alum/Ovalbumin Nanovaccine Boosts Cancer Metalloimmunotherapy Through Erythrocyte-Assisted Cascade Immune Activation.

Cancer therapeutic vaccines are powerful tools for immune system activation and eliciting protective responses against tumors. However, their efficacy has often been hindered by weak and slow immune responses. Here, the authors introduce an immunization strategy employing senescent erythrocytes to facilitate the accumulation of immunomodulatory zinc-Alum/ovalbumin (ZAlum/OVA) nanovaccines within both the spleen and solid tumors by temporarily saturating liver macrophages. This approach sets the stage for boosted cancer metalloimmunotherapy through a cascade immune activation. The accumulation of ZAlum/OVA nanovaccines in the spleen substantially enhances autophagy-dependent antigen presentation in dendritic cells, rapidly initiating OVA-specific T-cell responses against solid tumors. Concurrently, ZAlum/OVA nanovaccines accumulated in the tumor microenvironment trigger immunogenic cell death, leading to the induction of individualized tumor-associated antigen-specific T cell responses and increased T cell infiltration. This erythrocyte-assisted cascade immune activation using ZAlum/OVA nanovaccines results in rapid and robust antitumor immunity induction, holding great potential for clinical cancer metalloimmunotherapy.

Uncovering the relationship between floating marine litter and human activities in watersheds.

Rivers serve as the primary pathway for transporting floating marine litter (FML) from land to sea. However, the complex dynamics of transboundary rivers pose a significant obstacle when examining the impact of watershed-based human activities on FML distribution. This study conducts year-long monthly monitoring of FML using trawl and visual surveys in the coastal water of a peninsula dominated by indigenous rivers in south China. Overall, small pieces debris dominates FML in the nearshore waters of the peninsula, with meso-sized (0.5 cm-2.5 cm) FML accounting for 73.93 % of the total. The density of FML is more profoundly influenced by human activities within watersheds rather than its composition. Moreover, the association between human activity and FML density exhibits greater significant compared to variations based on geography and seasonality. This study provides a scientific basis for coastal protection and contributes for understanding of the mechanisms of marine litter transfer from land to sea.

Leveraging Coupling Effect-Enhanced Surface Plasmon Resonance of Ruthenium Nanocrystal-Decorated Mesoporous Silica Nanoparticles for Boosted Photothermal Immunotherapy.

Photothermal immunotherapy (PTI) has emerged as a promising approach for cancer treatment, while its efficacy is often hindered by the immunosuppressive tumor microenvironment (TME). Here, this work presents a multifunctional platform for tumor PTI based on ruthenium nanocrystal-decorated mesoporous silica nanoparticles (RuNC-MSN). By precisely regulating the distance between RuNC on MSN, this work achieves a remarkable enhancement in surface plasmon resonance of RuNC, leading to a significant improvement in the photothermal efficiency of RuNC-MSN. Furthermore, the inherent catalase-like activity of RuNC-MSN enables effective modulation of the immunosuppressive TME, thereby facilitating an enhanced immune response triggered by the photothermal effect-mediated immunogenic cell death (ICD). As a result, RuNC-MSN exhibits superior PTI performance, resulting in pronounced inhibition of primary tumor and metastasis. This study highlights the rational design of PTI agents with coupling effect-enhanced surface plasmon resonance, enabling simultaneous induction of ICD and regulation of the immunosuppressive TME, thereby significantly boosting PTI efficacy.

Spatial-Temporal Heterogeneity in Large Three-Dimensional Nanofibrillar Cellulose Hydrogel for Human Pluripotent Stem Cell Culture.

One approach to cell expansion is to use large hydrogel for growing a large number of cells. Nanofibrillar cellulose (NFC) hydrogel has been used for human induced pluripotent stem cell (hiPSCs) expansion. However, little is known about the status of hiPSCs at the single cell level inside large NFC hydrogel during culture. To understand the effect of NFC hydrogel property on temporal-spatial heterogeneity, hiPSCs were cultured in 0.8 wt% NFC hydrogel with different thicknesses with the top surface exposed to the culture medium. The prepared hydrogel exhibits less restriction in mass transfer due to the presence of macropores and micropores interconnecting the macropores. More than 85% of cells at different depths survive after 5 days of culture inside 3.5 mm thick hydrogel. Biological compositions at different zones inside the NFC gel were examined over time at a single-cell level. A dramatic concentration gradient of growth factors estimated in the simulation along 3.5 mm NFC hydrogel could be a reason for the spatial-temporal heterogeneity in protein secondary structure and protein glycosylation and pluripotency loss at the bottom zone. pH change caused by the lactic acid accumulation over time leads to changes in cellulose charge and growth factor potential, probably another reason for the heterogeneity in biochemical compositions. This study may help to develop optimal conditions for producing high-quality hiPSCs in large nanofibrillar cellulose hydrogel at scale.

Tracking the molecular evolution and transmission patterns of SARS-CoV-2 lineage B.1.466.2 in Indonesia based on genomic surveillance data.

BACKGROUND: As a new epi-center of COVID-19 in Asia and a densely populated developing country, Indonesia is facing unprecedented challenges in public health. SARS-CoV-2 lineage B.1.466.2 was reported to be an indigenous dominant strain in Indonesia (once second only to the Delta variant). However, it remains unclear how this variant evolved and spread within such an archipelagic nation. METHODS: For statistical description, the spatiotemporal distributions of the B.1.466.2 variant were plotted using the publicly accessible metadata in GISAID. A total of 1302 complete genome sequences of Indonesian B.1.466.2 strains with high coverage were downloaded from the GISAID's EpiCoV database on 28 August 2021. To determine the molecular evolutionary characteristics, we performed a time-scaled phylogenetic analysis using the maximum likelihood algorithm and called the single nucleotide variants taking the Wuhan-Hu-1 sequence as reference. To investigate the spatiotemporal transmission patterns, we estimated two dynamic parameters (effective population size and effective reproduction number) and reconstructed the phylogeography among different islands. RESULTS: As of the end of August 2021, nearly 85% of the global SARS-CoV-2 lineage B.1.466.2 sequences (including the first one) were obtained from Indonesia. This variant was estimated to account for over 50% of Indonesia's daily infections during the period of March-May 2021. The time-scaled phylogeny suggested that SARS-CoV-2 lineage B.1.466.2 circulating in Indonesia might have originated from Java Island in mid-June 2020 and had evolved into two disproportional and distinct sub-lineages. High-frequency non-synonymous mutations were mostly found in the spike and NSP3; the S-D614G/N439K/P681R co-mutations were identified in its larger sub-lineage. The demographic history was inferred to have experienced four phases, with an exponential growth from October 2020 to February 2021. The effective reproduction number was estimated to have reached its peak (11.18) in late December 2020 and dropped to be less than one after early May 2021. The relevant phylogeography showed that Java and Sumatra might successively act as epi-centers and form a stable transmission loop. Additionally, several long-distance transmission links across seas were revealed. CONCLUSIONS: SARS-CoV-2 variants circulating in the tropical archipelago may follow unique patterns of evolution and transmission. Continuous, extensive and targeted genomic surveillance is essential.

Early Spatiotemporal Patterns and Population Characteristics of the COVID-19 Pandemic in Southeast Asia.

This observational study aims to investigate the early disease patterns of coronavirus disease 2019 (COVID-19) in Southeast Asia, consequently providing historical experience for further interventions. Data were extracted from official websites of the WHO and health authorities of relevant countries. A total of 1346 confirmed cases of COVID-19, with 217 recoveries and 18 deaths, were reported in Southeast Asia as of 16 March 2020. The basic reproductive number (R0) of COVID-19 in the region was estimated as 2.51 (95% CI:2.31 to 2.73), and there were significant geographical variations at the subregional level. Early transmission dynamics were examined with an exponential regression model: y = 0.30e0.13x (p < 0.01, R2 = 0.96), which could help predict short-term incidence. Country-level disease burden was positively correlated with Human Development Index (r = 0.86, p < 0.01). A potential early shift in spatial diffusion patterns and a spatiotemporal cluster occurring in Malaysia and Singapore were detected. Demographic analyses of 925 confirmed cases indicated a median age of 44 years and a sex ratio (male/female) of 1.25. Age may play a significant role in both susceptibilities and outcomes. The COVID-19 situation in Southeast Asia is challenging and unevenly geographically distributed. Hence, enhanced real-time surveillance and more efficient resource allocation are urgently needed.

Molecular Phylogenesis and Spatiotemporal Spread of SARS-CoV-2 in Southeast Asia.

Background: The ongoing coronavirus disease 2019 (COVID-19) pandemic has posed an unprecedented challenge to public health in Southeast Asia, a tropical region with limited resources. This study aimed to investigate the evolutionary dynamics and spatiotemporal patterns of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the region. Materials and Methods: A total of 1491 complete SARS-CoV-2 genome sequences from 10 Southeast Asian countries were downloaded from the Global Initiative on Sharing Avian Influenza Data (GISAID) database on November 17, 2020. The evolutionary relationships were assessed using maximum likelihood (ML) and time-scaled Bayesian phylogenetic analyses, and the phylogenetic clustering was tested using principal component analysis (PCA). The spatial patterns of SARS-CoV-2 spread within Southeast Asia were inferred using the Bayesian stochastic search variable selection (BSSVS) model. The effective population size (Ne) trajectory was inferred using the Bayesian Skygrid model. Results: Four major clades (including one potentially endemic) were identified based on the maximum clade credibility (MCC) tree. Similar clustering was yielded by PCA; the first three PCs explained 46.9% of the total genomic variations among the samples. The time to the most recent common ancestor (tMRCA) and the evolutionary rate of SARS-CoV-2 circulating in Southeast Asia were estimated to be November 28, 2019 (September 7, 2019 to January 4, 2020) and 1.446 × 10-3 (1.292 × 10-3 to 1.613 × 10-3) substitutions per site per year, respectively. Singapore and Thailand were the two most probable root positions, with posterior probabilities of 0.549 and 0.413, respectively. There were high-support transmission links (Bayes factors exceeding 1,000) in Singapore, Malaysia, and Indonesia; Malaysia involved the highest number (7) of inferred transmission links within the region. A twice-accelerated viral population expansion, followed by a temporary setback, was inferred during the early stages of the pandemic in Southeast Asia. Conclusions: With available genomic data, we illustrate the phylogeography and phylodynamics of SARS-CoV-2 circulating in Southeast Asia. Continuous genomic surveillance and enhanced strategic collaboration should be listed as priorities to curb the pandemic, especially for regional communities dominated by developing countries.

Clinical features and Outcomes of Cryptococcemia patients with and without HIV infection.

BACKGROUND: The effects of cryptococcemia on patient outcomes in those with or without HIV remain unclear. METHODS: One hundred and seventy-nine cryptococcemia patients were enrolled in this retrospective study. Demographic characteristics, blood test results and outcome were compared between the two groups. RESULTS: The diagnosis time of Cryptococcus infection was 2.0(0-6.0) days for HIV-infected patients, 5.0 (1.5-8.0) days for HIV-uninfected patients (p = .008), 2.0 (1.0-6.0) days for cryptococcal meningitis (CM) patients and 6.0 (5.0-8.0) days for non-CM patients (p < .001). HIV infection [adjusted odds ratio (AOR) (95% confidence interval): 6.0(2.3-15.9)], CRP < 15 mg/L [AOR:3.7(1.7-8.1)) and haemoglobin > 110 g/L [AOR:2.5(1.2-5.4)] were risk factors for CM development. Forty-six (25.7%) patients died within 90 days. ICU stay [AOR:2.8(1.1-7.1)], hypoalbuminemia [AOR:2.7(1.4-5.3)], no anti-cryptococcal treatment [AOR:4.7(1.9-11.7)] and altered consciousness [AOR:2.4(1.0-5.5)] were independent risk factors for 90-day mortality in all patients. HIV infection did not increase the 90-day mortality of cryptococcemia patients when anti-Cryptococcus treatment was available. Non-Amphotericin B treatment [AOR:3.4(1.0-11.2)] was associated with 90-day mortality in HIV-infected patients, but age ≥ 50.0 years old [AOR:2.7(1.0-2.9)], predisposing disease [AOR:4.1(1.2-14.2)] and altered consciousness [AOR:3.7(1.1-12.9)] were associated with 90-day mortality in HIV-uninfected patients who accepted anti-Cryptococcus treatment. CONCLUSION: HIV infection increased the incidence of CM rather than mortality in cryptococcemia patients. The predictive model was completely divergent in HIV-infected and HIV-uninfected patients, suggesting that novel strategies for diagnosis and treatment algorithms are urgently needed.

Incidence and Risk Factors for Suicide Death among Kaposi's Sarcoma Patients: A Surveillance, Epidemiology, and End Results Analysis.

BACKGROUND The suicide risk of patients with cancer is higher than the general population. Our research aimed to explore the Surveillance, Epidemiology, and End Results (SEER) database to define incidence and quest risk factors for death of suicide in patients with Kaposi's sarcoma (KS) in the United States (US). MATERIAL AND METHODS We screened KS patients without human immunodeficiency virus status in the SEER database from 1980 to 2016, calculated the standardized mortality ratios of them by comparing the rates with those of the US general population from 1980 to 2016, and identified relevant suicide risk factors by univariable and multivariable logistic regression analyses. RESULTS The suicide rates of KS patients and US general population were 115.31 (110 suicides among 21 405 patients) and 15.1 per 100 000 person-years, respectively, thus the standardized mortality ratio was 7.64 (95% confidence interval [CI], 6.28-9.21). The multivariate analysis showed that black race (versus white race, hazard ratio [HR]: 0.43, 95% CI: 0.21-0.89, P=0.022), advanced age at diagnosis (≥55 years versus 18-44 years, HR: 0.31, 95% CI: 0.14-0.66, P=0.002), and chemotherapy (versus no chemotherapy, HR: 0.60, 95% CI: 0.37-0.96, P=0.032) were protective factors for suicide among KS patients. CONCLUSIONS Clinicians and caregivers can apply our findings to identify KS patients with high suicide risk characteristics (white race, age of 18-44 years, non-chemotherapy) and exert timely interventions during patient diagnosis, treatment, and follow-up to reduce the suicide rate in this population.

The conservation value of elevation data accuracy and model sophistication in reserve design under sea-level rise.

Many studies have explored the value of using more sophisticated coastal impact models and higher resolution elevation data in sea-level rise (SLR) adaptation planning. However, we know little about to what extent the improved models and data could actually lead to better conservation outcomes under SLR. This is important to know because high-resolution data are likely to not be available in some data-poor coastal areas in the world and running more complicated coastal impact models is relatively time-consuming, expensive, and requires assistance by qualified experts and technicians. We address this research question in the context of identifying conservation priorities in response to SLR. Specifically, we investigated the conservation value of using more accurate light detection and ranging (Lidar)-based digital elevation data and process-based coastal land-cover change models (Sea Level Affecting Marshes Model, SLAMM) to identify conservation priorities versus simple "bathtub" models based on the relatively coarse National Elevation Dataset (NED) in a coastal region of northeast Florida. We compared conservation outcomes identified by reserve design software (Zonation) using three different model dataset combinations (Bathtub-NED, Bathtub-Lidar, and SLAMM-Lidar). The comparisons show that the conservation priorities are significantly different with different combinations of coastal impact models and elevation dataset inputs. The research suggests that it is valuable to invest in more accurate coastal impact models and elevation datasets in SLR adaptive conservation planning because this model-dataset combination could improve conservation outcomes under SLR. Less accurate coastal impact models, including ones created using coarser Digital Elevation Model (DEM) data can still be useful when better data and models are not available or feasible, but results need to be appropriately assessed and communicated. A future research priority is to investigate how conservation priorities may vary among different SLR scenarios when different combinations of model-data inputs are used.