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Soil stabilization technology based on microbial-induced carbonate precipitation (MICP) has gained widespread interest in geotechnical engineering. MICP has been found to be able to improve soil strength, stiffness, liquefaction resistance, erosion resistance, while maintaining a good permeability simultaneously. MICP processes involves a series of biochemical reactions that are affected by many factors, both intrinsically and externally. This paper reviews various influential factors for MICP process, including bacterial species, concentration of bacteria, temperature, pH, composition and concentration of cementation solution, grouting strategies, and soil properties. Through this comprehensive review, we find that: (1) the species and strains of bacteria, concentration of bacteria solution, temperature, pH value, and the cementation solution properties all affect the characteristics of formed calcium carbonate, such as crystal type, appearance and size, which consequently affect the cementation degree and distribution in geomaterials; (2) the condition with temperature between 20 and 40 °C, pH between 7 and 9.5, the concentration of the cementation solution within 1 mol/L, and high bacteria concentration is optimal for applying MICP in soil. Under the optimal condition, relatively low temperature, high pH value, and low concentration of cementation solution could help retain permeability and vice versa; (3) the effective grain size ranging from 10 to 1000 µm. MICP treatment works most effectively for larger size, well-graded sand; (4) the multi-phase, multi-concentration or electroosmotic grouting method can improve the MICP treatment efficiency. The grouting velocity below 0.042 mol/L/h is beneficial for improving the utilization ratio of cementation solution. The recommended grouting pressure is generally between 0.1 and 0.3 bar for MICP applications in sand and should not exceed 1.1 bar for silty and clayey soils.

With the huge therapeutic potential, cancer immunotherapy is expected to become the mainstream of cancer treatment. In the current field of cancer immunotherapy, there are mainly five types. Immune checkpoint blockade therapy is one of the most promising directions. Adoptive cell therapy is an important component of cancer immunotherapy. The therapy with the cancer vaccine is promising cancer immunotherapy capable of cancer prevention. Cytokine therapy is one of the pillars of cancer immunotherapy. Oncolytic immunotherapy is a promising novel component of cancer immunotherapy, which with significantly lower incidence of serious adverse reactions. The recent positive results of many clinical trials with cancer immunotherapy may herald good clinical prospects. But there are still many challenges in the broad implementation of immunotherapy. Such as the immunotherapy cannot act on all tumors, and it has serious adverse effects including but not limited to nonspecific and autoimmunity inflammation. Here, we center on recent progress made within the last 5 years in cancer immunotherapy. And we discuss the theoretical background, as well as the opportunities and challenges of cancer immunotherapy.

Drought is a serious global environmental issue that causes water resource scarcity and threatens agriculture and food supplements. This study aims to investigate the long‐term performance of an eco‐friendly technique‐microbial induced carbonate precipitation (MICP) on drought mitigation at field and laboratory scales. Seven in‐situ slopes treated with different MICP rounds and cementation solution concentrations were subjected to 16‐month weathering. Tests were conducted to evaluate the evaporation characteristics, water retention capacity, and CaCO3 distribution. Laboratory soil samples were further prepared to provide evidence related to underlying weathering mechanisms. The results show that MICP has a time‐dependent performance on drought mitigation. After MICP treatment, soil performs a remarkable evaporation suppression ability and the evaporation rate can decrease by 50%. This is attributed to the soluble salts which increase soil water retention capability and dense hard crust which inhibits water vapor migration into the atmosphere. However, the soluble salts and crust are sensitive to weathering thus leading to degradation of MICP. Suffering 16‐month weathering, the MICP‐induced CaCO3 decreases by more than 60%. The evaporation rate of soil increases with MICP rounds and cementation solution concentrations and can reach nearly two times of untreated soil. MICP‐treated field soil exhibits weaker water retention capacity than untreated soil because MICP alters soil microstructure which expands macropores and decreases volume of micropores. Connected macropores act as favorable evaporation channels and accelerate evaporation. To ensure MICP long‐term effects, periodical treatments are necessary. The most effective MICP treatment scheme is four to six treatment rounds and 1.0 M cementation solution. Key Points The eco‐friendly technique‐microbial induced carbonate precipitation (MICP) performs the time‐dependence on long‐term drought mitigation MICP technique exhibits a remarkable evaporation reduction capacity which is attributed to the presence of soluble salts and hard crust This study brings new insights into drought mitigation through a bio‐approach and shows the potential for in‐situ practice

Due to more extreme weather events and accelerating sea-level rise, coastal sand dunes are subjected to more frequent storm wave inundation and surge impacts, which contribute to widespread coastal erosion problems. In this study, two novel bio-mediated methods, microbial-induced carbonate precipitation (MICP) and enzymatic-induced carbonate precipitation (EICP), were investigated and compared for their effectiveness in mitigating sand dune erosion under wave attack. Small-scale laboratory model tests were performed on MICP-treated, EICP-treated, and untreated sand dunes at dune slope angles and two wave intensities for up to 2 h. The cross-shore profile was captured continuously during the course of the erosion test. The erosion volume above the still water level (SWL) and landward retreat distance at the SWL were calculated based on the captured bed profiles. The results show that both EICP and MICP could substantially reduce sand dune erosion at mild-to-moderate wave and dune slope conditions. However, the effectiveness of MICP treatment deteriorated at steeper dune slopes with longer period of wave attack. Under the most adverse condition (i.e., steepest dune slope, biggest wave, and longest period of wave attack), neither EICP nor MICP could effectively mitigate erosion. Fundamentally, the variable effectiveness of MICP and EICP treatment for sand dune erosion control was attributed to the spatial distribution pattern of formed calcite precipitation, which was determined by the way how EICP and MICP were applied. The calcite precipitation was relatively uniform in EICP-treated sand dunes. In MICP-treated ones, however, substantial calcite precipitation concentrated in the shallow surface layer as confirmed by the surface penetration test and SEM observation.

In response to Taiwan’s rapidly aging population and the rising demand for personalized health care, accurately assessing individual physiological aging has become an essential area of study. This research utilizes health examination data to propose a machine learning-based biological age prediction model that quantifies physiological age through residual life estimation. The model leverages LightGBM, which shows an 11.40% improvement in predictive performance (R-squared) compared to the XGBoost model. In the experiments, the use of MICE imputation for missing data significantly enhanced prediction accuracy, resulting in a 23.35% improvement in predictive performance. Kaplan-Meier (K-M) estimator survival analysis revealed that the model effectively differentiates between groups with varying health levels, underscoring the validity of biological age as a health status indicator. Additionally, the model identified the top ten biomarkers most influential in aging for both men and women, with a 69.23% overlap with Taiwan’s leading causes of death and previously identified top health-impact factors, further validating its practical relevance. Through multidimensional health recommendations based on SHAP and PCC interpretations, if the health recommendations provided by the model are implemented, 64.58% of individuals could potentially extend their life expectancy. This study provides new methodological support and data backing for precision health interventions and life extension.

Acute pancreatitis (AP) is a common cause of a clinically acute abdomen. Crosstalk between acinar cells and leukocytes (especially macrophages) plays an important role in the development of AP. However, the mechanism mediating the interaction between acinar cells and macrophages is still unclear. This study was performed to explore the role of acinar cell extracellular vesicles (EVs) in the crosstalk between acinar cells and macrophages involved in the pathogenesis of AP. EVs derived from caerulein-treated acinar cells induced macrophage infiltration and aggravated pancreatitis in an AP rat model. Further research showed that acinar cell-derived EV miR-183-5p led to M1 macrophage polarization by downregulating forkhead box protein O1 (FoxO1), and a dual-luciferase reporter assay confirmed that FoxO1 was directly inhibited by miR-183-5p. In addition, acinar cell-derived EV miR-183-5p reduced macrophage phagocytosis. Acinar cell-derived EV miR-183-5p promoted the pancreatic infiltration of M1 macrophages and increased local and systemic damage in vivo . Subsequently, miR-183-5p overexpression in macrophages induced acinar cell damage and trypsin activation, thus further exacerbating the disease. In clinical samples, elevated miR-183-5p levels were detected in serum EVs and positively correlated with the severity of AP. EV miR-183-5p might play an important role in the development of AP by facilitating M1 macrophage polarization, providing a new insight into the diagnosis and targeted management of pancreatitis. Graphical abstract of the present study. In our caerulein-induced AP model, miR-183-5p was upregulated in injured acinar cells and transported by EVs to macrophages. miR-183-5p could induce M1 macrophage polarization through downregulation of FoxO1 and the release of inflammatory cytokines, which could aggravate AP-related injuries. Therefore, a vicious cycle might exist between injured ACs and M1 macrophage polarization, which is fulfilled by EV-transported miR-183-5p, leading to sustainable and progressive AP-related injuries.

Sepsis, a critical global health challenge, accounted for approximately 20% of worldwide deaths in 2017. Although the Sequential Organ Failure Assessment (SOFA) score standardizes the diagnosis of organ dysfunction, early sepsis detection remains challenging due to its insidious symptoms. Current diagnostic methods, including clinical assessments and laboratory tests, frequently lack the speed and specificity needed for timely intervention, particularly in vulnerable populations such as older adults, intensive care unit (ICU) patients, and those with compromised immune systems. While bacterial cultures remain vital, their time-consuming nature and susceptibility to false negatives limit their effectiveness. Even promising existing machine learning approaches are restricted by reliance on complex clinical factors that could delay results, underscoring the need for faster, simpler, and more reliable diagnostic strategies. This study introduces innovative machine learning models using complete blood count with differential (CBC+DIFF) data-a routine, minimally invasive test that assesses immune response through blood cell measurements, critical for sepsis identification. The primary objective was to implement this model within an artificial intelligence-clinical decision support system (AI-CDSS) to enhance early sepsis detection and management in critical care settings. This retrospective study at Tri-Service General Hospital (September to December 2023) analyzed 746 ICU patients with suspected pneumonia-induced sepsis (supported by radiographic evidence and a SOFA score increase of ≥2 points), alongside 746 stable outpatients as controls. Sepsis infection sources were confirmed through positive sputum, blood cultures, or FilmArray results. The dataset incorporated both basic hematological factors and advanced neutrophil characteristics (side scatter light intensity, cytoplasmic complexity, and neutrophil-to-lymphocyte ratio), with data from September to November used for training and data from December used for validation. Machine learning models, including light gradient boosting machine (LGBM), random forest classifier, and gradient boosting classifier, were developed using CBC+DIFF data and were assessed using metrics such as area under the curve, sensitivity, and specificity. The best-performing model was integrated into the AI-CDSS, with its implementation supported through workshops and training sessions. Pathogen identification in ICU patients found 243 FilmArray-positive, 411 culture-positive, and 92 undetected cases, yielding a final dataset of 654 (43.8%) sepsis cases out of 1492 total cases. The machine learning models demonstrated high predictive accuracy, with LGBM achieving the highest area under the curve (0.90), followed by the random forest classifier (0.89) and gradient boosting classifier (0.88). The best-performing LGBM model was selected and integrated as the core of our AI-CDSS, which was built on a web interface to facilitate rapid sepsis risk assessment using CBC+DIFF data. This study demonstrates that by providing streamlined predictions using CBC+DIFF data without requiring extensive clinical parameters, the AI-CDSS can be seamlessly integrated into clinical workflows, enhancing rapid, accurate identification of sepsis and improving patient care and treatment timeliness.

•Magnetic fields have a minor effect on the early development of zebrafish.•Moderate static magnetic fields enhance the inflammatory responses in zebrafish.•Ultrahigh magnetic fields have little effect on inflammatory response of zebrafish.•Magnetic fields may affect the immune function of zebrafish by regulating melatonin. Magnetic Resonance Imaging (MRI) is widely applied in medical diagnosis due to its excellent non-invasiveness. With the increasing intensity of static magnetic field (SMF), the safety assessment of MRI has been ongoing. In this study, zebrafish larvae were exposed to SMFs of 0.4, 3.0, and 9.4 T for 2 h (h), and we found that there was no significant difference in the number of spontaneous tail swings, heart rate, and body length of zebrafish larvae in the treatment groups. The expression of development-related genes shha, pygo1, mylz3 and runx2b in the three SMF groups was almost not significantly different from the control group. Behavior tests unveiled a notable reduction in both the average speed and duration of high-speed movements in zebrafish larvae across all three SMF groups. In addition, the 0.4 and 3.0 T SMFs increased the migration of neutrophils in caudal fin injury, and the expression of pro-inflammatory cytokines was also increased. To explore the mechanism of SMFs on zebrafish immune function, this study utilized aanat2−/− mutant fish to demonstrate the effect of melatonin (MT) involvement in SMFs on zebrafish immune function. This study provides experimental data for understanding the effects of SMFs on organisms, and also provides a new insight for exploring the relationship between magnetic fields and immune function. [Display omitted]

The biological mechanisms linking air pollution to cardiovascular events still remain largely unclear. To investigate whether biological mechanisms linking air pollution to cardiovascular events occurred concurrently in human subjects exposed to urban air pollutants. We recruited a panel of 76 young, healthy students from a university in Taipei. Between April and June of 2004 or 2005, three measurements were made in each participant of high-sensitivity C-reactive protein (hs-CRP), 8-hydroxy-2'-deoxyguanosine (8-OHdG), plasminogen activator fibrinogen inhibitor-1 (PAI-1), tissue-type plasminogen activator (tPA) in plasma, and heart rate variability (HRV). Gaseous air pollutants were measured at one air-monitoring station inside their campus, and particulate air pollutants were measured at one particulate matter supersite monitoring station 1 km from their campus. We used linear mixed-effects models to associate biological endpoints with individual air pollutants averaged over 1- to 3-day periods before measurements were performed. We found that increases in hs-CRP, 8-OHdG, fibrinogen, and PAI-1, and decreases in HRV indices were associated with increases in levels of particles with aerodynamic diameters less than 10 microm and 2.5 microm, sulfate, nitrate, and ozone (O(3)) in single-pollutant models. The increase in 8-OHdG, fibrinogen, and PAI-1, and the reduction in HRV remained significantly associated with 3-day averaged sulfate and O(3) levels in two-pollutant models. There were moderate correlations (r = -0.3) between blood markers of hs-CRP, fibrinogen, PAI-1, and HRV indices. Urban air pollution is associated with inflammation, oxidative stress, blood coagulation and autonomic dysfunction simultaneously in healthy young humans, with sulfate and O(3) as two major traffic-related pollutants contributing to such effects.

IntroductionThe COVID-19 pandemic caused a healthcare crisis in China and continues to wreak havoc across the world. This paper evaluated COVID-19’s impact on national and regional healthcare service utilisation and expenditure in China.MethodsUsing a big data approach, we collected data from 300 million bank card transactions to measure individual healthcare expenditure and utilisation in mainland China. Since the outbreak coincided with the 2020 Chinese Spring Festival holiday, a difference-in-difference (DID) method was employed to compare changes in healthcare utilisation before, during and after the Spring Festival in 2020 and 2019. We also tracked healthcare utilisation before, during and after the outbreak.ResultsHealthcare utilisation declined overall, especially during the post-festival period in 2020. Total healthcare expenditure and utilisation declined by 37.8% and 40.8%, respectively, while per capita expenditure increased by 3.3%. In a subgroup analysis, we found that the outbreak had a greater impact on healthcare utilisation in cities at higher risk of COVID-19, with stricter lockdown measures and those located in the western region. The DID results suggest that, compared with low-risk cities, the pandemic induced a 14.8%, 26.4% and 27.5% reduction in total healthcare expenditure in medium-risk and high-risk cities, and in cities located in Hubei province during the post-festival period in 2020 relative to 2019, an 8.6%, 15.9% and 24.4% reduction in utilisation services; and a 7.3% and 18.4% reduction in per capita expenditure in medium-risk and high-risk cities, respectively. By the last week of April 2020, as the outbreak came under control, healthcare utilisation gradually recovered, but only to 79.9%–89.3% of its pre-outbreak levels.ConclusionThe COVID-19 pandemic had a significantly negative effect on healthcare utilisation in China, evident by a dramatic decline in healthcare expenditure. While the utilisation level has gradually increased post-outbreak, it has yet to return to normal levels.