Daily Online Adaptive Radiation Therapy of Postoperative Endometrial and Cervical Cancer With PTV Margin Reduction to 5 mm: Dosimetric Outcomes, Acute Toxicity, and First Clinical Experience.

Purpose: This study evaluated the first clinical implementation of daily iterative cone beam computed tomography (iCBCT)-guided online adaptive radiation therapy (oART) in the postoperative treatment of endometrial and cervical cancer. Methods and Materials: Seventeen consecutive patients treated with daily iCBCT-guided oART were enrolled in this prospective study, with a reduced uniform 3-dimensional PTV margin of 5 mm. Treatment plans were designed to deliver 45 or 50.4 Gy in 1.8 Gy daily fractions to PTV. Pre- and posttreatment ultrasound and iCBCT scans were performed to record intrafractional bladder and rectal volume changes. The accuracy of contouring, oART procedure time, dosimetric outcomes, and acute toxicity were evaluated. Results: The average time from first iCBCT acquisition to completion of treatment was 22 minutes and 26 seconds. During this period, bladder volume increased by 44 cm3 using iCBCT contouring, whereas rectal volume remained stable (62.9 cm3 pretreatment vs 61.9 cm3 posttreatment). A total of 91.6% of influencers and 88.1% of CTVs required no or minor edits. The adapted plan was selected in all (434) fractions and significantly improved the dosimetry coverage for CTV and PTV, especially the vaginal PTV coverage by nearly 7% (P < .05). The adapted bladder Dmean was 104.61 cGy, and the rectum Dmean was 123.67 cGy, significantly lower than the scheduled plan of 108.24 and 128.19 cGy, respectively. The bone marrow and femur head left and right dosimetry were also improved with adaptation. Grade 2 acute gastrointestinal and genitourinary toxicities were 24% and 0, respectively. There was a grade 3 acute toxicity of decreased white blood cell count in 1 patient. Conclusions: Daily oART was associated with favorable dosimetry improvement and low acute toxicity, supporting its safety and efficacy for postoperative treatment of endometrial and cervical cancer. These results need to be validated in a larger prospective randomized controlled cohort.

Cold unfolding of heat-responsive TRPV3.

The homotetrameric thermosensitive transient receptor potential vanilloid 1-4 (TRPV1-4) channels in sensory neurons are strongly responsive to heat stimuli. However, their cold activations have not been reported in line with the nonzero heat capacity difference during heat or cold unfolding transitions. Here, along with the experimental examinations of the predicted ring size changes in different domains against the central pore during channel gating at various temperatures, the K169A mutant of reduced human TRPV3 was first found to be activated and inactivated by cold below 42°C. Further thermoring analyses revealed distinct heat and cold unfolding pathways, which resulted in different protein thermostabilities. Thus, both cold and heat unfolding transitions of thermosensitive TRPV1-4 channels may exist once a mutation destabilizes the closed state.

Prognostic model incorporating immune checkpoint genes to predict the immunotherapy efficacy for lung adenocarcinoma: a cohort study integrating machine learning algorithms.

This study aimed to develop and validate a nomogram based on immune checkpoint genes (ICGs) for predicting prognosis and immune checkpoint blockade (ICB) efficacy in lung adenocarcinoma (LUAD) patients. A total of 385 LUAD patients from the TCGA database and 269 LUAD patients in the combined dataset (GSE41272 + GSE50081) were divided into training and validation cohorts, respectively. Three different machine learning algorithms including random forest (RF), least absolute shrinkage and selection operator (LASSO) logistic regression analysis, and support vector machine (SVM) were employed to select the predictive markers from 82 ICGs to construct the prognostic nomogram. The X-tile software was used to stratify patients into high- and low-risk subgroups based on the nomogram-derived risk scores. Differences in functional enrichment and immune infiltration between the two subgroups were assessed using gene set variation analysis (GSVA) and various algorithms. Additionally, three lung cancer cohorts receiving ICB therapy were utilized to evaluate the ability of the model to predict ICB efficacy in the real world. Five ICGs were identified as predictive markers across all three machine learning algorithms, leading to the construction of a nomogram with strong potential for prognosis prediction in both the training and validation cohorts (all AUC values close to 0.800). The patients were divided into high- (risk score ≥ 185.0) and low-risk subgroups (risk score < 185.0). Compared to the high-risk subgroup, the low-risk subgroup exhibited enrichment in immune activation pathways and increased infiltration of activated immune cells, such as CD8 + T cells and M1 macrophages (P < 0.05). Furthermore, the low-risk subgroup had a greater likelihood of benefiting from ICB therapy and longer progression-free survival (PFS) than did the high-risk subgroup (P < 0.05) in the two cohorts receiving ICB therapy. A nomogram based on ICGs was constructed and validated to aid in predicting prognosis and ICB treatment efficacy in LUAD patients.

Network pharmacology combined with an experimental validation study to reveal the effect and mechanism of Lonicera japonica Thunb. extracts against immunomodulation.

Lonicera japonica Thunb. (LJT) is known for its valuable medicinal properties that highlight its potential application in the pharmaceutical and health food industry. We predict that LJT polyphenols by network pharmacology may be involved in immunomodulation, and the study of LJT polyphenols regulating immunity is still insufficient; therefore, we experimentally found that LJT enhances immunity by promoting the proliferation and phagocytic activity of RAW246.7 cells. A model of an immunosuppressed mouse was constructed using cyclophosphamide-induced, and LJT was extracted for the intervention. We found that LJT restored immune homeostasis in immune deficiency mice by inhibiting the abnormal apoptosis in lymphocytes, enhancing natural killer cell cytotoxicity, promoting T lymphocyte proliferation, and increasing the CD4+ and CD8+ T lymphocytes in quantity. Moreover, LJT treatment modulates immunity by significantly downregulating lipopolysaccharide-induced inflammation and oxidative stress levels. We verified the immunomodulatory function of LJT through both cell and animal experiments. The combination of potential-protein interactions and molecular docking later revealed that LJT polyphenols were associated with immunomodulatory effects on MAPK1; together, LJT intervention significantly modulates the immune, with the activation of MAPK1 as the underlying mechanism of action, which provided evidence for the utilization of LJT as a nutraceutical in immune function.

Extracorporeal closed-loop respiratory regulation for patients with respiratory difficulty using a soft bionic robot.

OBJECTIVE: Respiratory regulation is critical for patients with respiratory dysfunction. Clinically used ventilators can lead to long-term dependence and injury. Extracorporeal assistance approaches such as iron-lung devices provide a noninvasive alternative, however, artificial actuator counterparts have not achieved marvelous biomimetic ventilation as human respiratory muscles. Here, we propose a bionic soft exoskeleton robot that can achieve extracorporeal closed-loop respiratory regulation by emulating natural human breath. METHODS: For inspiration, a soft vacuum chamber is actuated to produce negative thoracic pressure and thus expand lung volume by pulling the rib cage up and outward through use of external negative pressure. For expiration, a soft origami array under positive pressure pushes the abdominal muscles inward and the diaphragm upward. To achieve in vitro measurement of respiratory profile, we describe a wireless respiratory monitoring device to measure respiratory profiles with high accuracy, validated by quantitative comparisons with spirometer as gold-standard reference. By constructing a human-robot coupled respiratory mechanical model, a model-based proportional controller is designed for continuous tracking of the target respiratory profile. RESULTS: In experiments with ten healthy participants and ten patients with respiratory difficulty, the robot can adjust its assistive forces in real time and drive human-robot coupling respiratory system to track the target profile. CONCLUSION: The biomimetic robot can achieve extracorporeal closed-loop respiratory regulation for a diverse population. SIGNIFICANCE: The soft robot has important potential to assist respiration for people with respiratory difficulty, whether in a hospital or a home setting.

Based on scRNA-seq and bulk RNA-seq to establish tumor immune microenvironment-associated signature of skin melanoma and predict immunotherapy response.

Skin cutaneous melanoma (SKCM), a form of skin cancer, ranks among the most formidable and lethal malignancies. Exploring tumor microenvironment (TME)-based prognostic indicators would help improve the efficacy of immunotherapy for SKCM patients. This study analyzed SKCM scRNA-seq data to cluster non-malignant cells that could be used to explore the TME into nine immune/stromal cell types, including B cells, CD4 T cells, CD8 T cells, dendritic cells, endothelial cells, Fibroblasts, macrophages, neurons, and natural killer (NK) cells. Using data from The Cancer Genome Atlas (TCGA), we employed SKCM expression profiling to identify differentially expressed immune-associated genes (DEIAGs), which were then incorporated into weighted gene co-expression network analysis (WGCNA) to investigate TME-associated hub genes. Discover candidate small molecule drugs based on pivotal genes. Tumor immune microenvironment-associated genes (TIMAGs) for constructing TIMAS were identified and validated. Finally, the characteristics of TIAMS subgroups and the ability of TIMAS to predict immunotherapy outcomes were analyzed. We identified five TIMAGs (CD86, CD80, SEMA4D, C1QA, and IRF1) and used them to construct TIMAS. In addition, five potential SKCM drugs were identified. The results showed that TIMAS-low patients were associated with immune-related signaling pathways, high MUC16 mutation frequency, high T cell infiltration, and M1 macrophages, and were more favorable for immunotherapy. Collectively, TIMAS constructed by comprehensive analysis of scRNA-seq and bulk RNA-seq data is a promising marker for predicting ICI treatment outcomes and improving individualized therapy for SKCM patients.

Assessment of Key Factors Impacting Variability in AAV Vector Genome Titration by Digital PCR.

Recombinant adeno-associated virus (rAAV) has emerged as a prominent vector for in vivo gene therapy, owing to its distinct advantages. Accurate determination of the rAAV genome titer is crucial for ensuring the safe and effective administration of clinical doses. The evolution of the rAAV genome titer assay from quantitative PCR (qPCR) to digital PCR (dPCR) has enhanced accuracy and precision, yet practical challenges persist. This study systematically investigated the impact of various operational factors on genome titration in a single-factor manner, aiming to address potential sources of variability in the quantitative determination process. Our findings revealed that a pretreatment procedure without genome extraction exhibits superior precision compared with titration with genome extraction. Additionally, notable variations in titration results across different brands of dPCR instruments were documented, with relative standard deviation (RSD) reaching 23.47% for AAV5 and 11.57% for AAV8. Notably, optimal operations about DNase I digestion were identified; we thought treatment time exceeding 30 min was necessary, and there was no need for thermal inactivation after digestion. And we highlighted that thermal capsid disruption before serial dilution substantially affected AAV genome titers, causing a greater than ten-fold decrease. Conversely, this study found that additive components of dilution buffer are not significant contributors to titration variations. Furthermore, we found that repeated freeze-thaw cycles significantly compromised AAV genome titers. In conclusion, a comprehensive dPCR titration protocol, incorporating insights from these impact factors, was proposed and successfully tested across multiple serotypes of AAV. The results demonstrate acceptable variations, with the RSD consistently below 5.00% for all tested AAV samples. This study provides valuable insights to reduce variability and improve the reproducibility of AAV genome titration using dPCR.

Ultrasound-Assisted Extraction of Phenolic Compounds from Celtuce (Lactuca sativa var. augustana) Leaves Using Natural Deep Eutectic Solvents (NADES): Process Optimization and Extraction Mechanism Research.

Natural deep eutectic solvents (NADESs), as emerging green solvents, can efficiently extract natural products from natural resources. However, studies on the extraction of phenolic compounds from celtuce (Lactuca sativa var. augustana) leaves (CLs) by NADESs are still lacking. This study screened the NADES L-proline-lactic acid (Pr-LA), combined it with ultrasound-assisted extraction (UAE) to extract phenolic compounds from CLs, and conducted a comparative study on the extraction effect with traditional extraction solvents. Both SEM and FT-IR confirmed that Pr-LA can enhance the degree of fragmentation of cell structures and improve the extraction rate of phenolic compounds. Molecular dynamics simulation results show that Pr-LA can improve the solubility of phenolic compounds and has stronger hydrogen bonds and van der Waals interactions with phenolic compounds. Single-factor and Box-Behnken experiments optimized the process parameters for the extraction of phenolic compounds from CLs. The second-order kinetic model describes the extraction process of phenolic compounds from CLs under optimal process parameters and provides theoretical guidance for actual industrial production. This study not only provides an efficient and green method for extracting phenolic compounds from CLs but also clarifies the mechanism of improved extraction efficiency, which provides a basis for research on the NADES extraction mechanism.

County land use carbon emission and scenario prediction in Mianyang Science and Technology City New District, Sichuan Province, China.

The role of carbon emissions resulting from land use change in the compilation of national greenhouse gas emission inventories is of paramount significance. This study is centered on the Mianyang Science and Technology City New Area located in Sichuan Province, China. We used the CLUE-S model and Sentinel-2A remote sensing data from 2017 to simulate and validate land use changes in 2022. Based on this validation, we established three simulation scenarios: a baseline scenario, an agricultural development scenario, and a construction development scenario. Using remote sensing data from 2022, we projected the land use for 2030. We also used CO2 concentration data collected in 2022 and 2023, processed the data using ArcGIS and Python, and conducted a quantitative analysis of carbon emissions under each scenario. Ultimately, the accuracy of both measured and predicted CO2 values for 2023 was juxtaposed and authenticated, thus concluding the investigative cycle of this study. Key findings include: (1) The accuracy of the CLUE-S model in the study area was assessed using overall accuracy, quantity disagreement and allocation disagreement indexes. In 2022, the overall accuracy is 98.19%, the quantity disagreement is 1.7%, and the allocation disagreement is 2.2%. (2) Distinct land resource utilization characteristics in scenarios, highlighting potential impacts on economic development and pollution. (3) Increased carbon emissions across scenarios, with construction development showing the highest rise (4.170%) and agricultural development the lowest (0.766%). (4) The predictive accuracy of the validation group's CO2 concentration values can reach 99.5%. This study proposes precise CO2 prediction at the county level, thus laying the groundwork for future research endeavors. Such findings are indispensable for informing carbon policy formulation and promoting low-carbon development strategies.

Predictive Model to Identify the Long Time Survivor in Patients with Glioblastoma: A Cohort Study Integrating Machine Learning Algorithms.

We aimed to develop and validate a predictive model for identifying long-term survivors (LTS) among glioblastoma (GB) patients, defined as those with an overall survival (OS) of more than 3 years. A total of 293 GB patients from CGGA and 169 from TCGA database were assigned to training and validation cohort, respectively. The differences in expression of immune checkpoint genes (ICGs) and immune infiltration landscape were compared between LTS and short time survivor (STS) (OS<1.5 years). The differentially expressed genes (DEGs) and weighted gene co-expression network analysis (WGCNA) were used to identify the genes differentially expressed between LTS and STS. Three different machine learning algorithms were employed to select the predictive genes from the overlapping region of DEGs and WGCNA to construct the nomogram. The comparison between LTS and STS revealed that STS exhibited an immune-resistant status, with higher expression of ICGs (P<0.05) and greater infiltration of immune suppression cells compared to LTS (P<0.05). Four genes, namely, OSMR, FMOD, CXCL14, and TIMP1, were identified and incorporated into the nomogram, which possessed good potential in predicting LTS probability among GB patients both in the training (C-index, 0.791; 0.772-0.817) and validation cohort (C-index, 0.770; 0.751-0.806). STS was found to be more likely to exhibit an immune-cold phenotype. The identified predictive genes were used to construct the nomogram with potential to identify LTS among GB patients.

Pressure-Induced Enhancement and Retainability of Optoelectronic Properties in Layered Zirconium Disulfide.

Transition metal dichalcogenides (TMDs) exhibit excellent electronic and photoelectric properties under pressure, prompting researchers to investigate their structural phase transitions, electrical transport, and photoelectric response upon compression. Herein, the structural and photoelectric properties of layered ZrS2 under pressure using in situ high-pressure photocurrent, Raman scattering spectroscopy, alternating current impedance spectroscopy, absorption spectroscopy, and theoretical calculations are studied. The experimental results show that the photocurrent of ZrS2 continuously increases with increasing pressure. At 24.6 GPa, the photocurrent of high-pressure phase P21/m is three orders of magnitude greater than that of the initial phase P 3 ¯ m 1 $P\bar{3}m1$ at ambient pressure. The minimum synthesis pressure for pure high-pressure phase P21/m of ZrS2 is 18.8 GPa, which exhibits a photocurrent that is two orders of magnitude higher than that of the initial phase P 3 ¯ m 1 $P\bar{3}m1$ and displays excellent stability. Additionally, it is discovered that the crystal structure, electrical transport properties and bandgap of layered ZrS2 can also be regulated by pressure. This work offers researchers a new direction for synthesizing high-performance TMDs photoelectric materials using high pressure, which is crucial for enhancing the performance of photoelectric devices in the future.

Pelvic target volume inter-fractional motion during radiotherapy for cervical cancer with daily iterative cone beam computed tomography.

BACKGROUND: Tumor regression and organ movements indicate that a large margin is used to ensure target volume coverage during radiotherapy. This study aimed to quantify inter-fractional movements of the uterus and cervix in patients with cervical cancer undergoing radiotherapy and to evaluate the clinical target volume (CTV) coverage. METHODS: This study analyzed 303 iterative cone beam computed tomography (iCBCT) scans from 15 cervical cancer patients undergoing external beam radiotherapy. CTVs of the uterus (CTV-U) and cervix (CTV-C) contours were delineated based on each iCBCT image. CTV-U encompassed the uterus, while CTV-C included the cervix, vagina, and adjacent parametrial regions. Compared with the planning CTV, the movement of CTV-U and CTV-C in the anterior-posterior, superior-inferior, and lateral directions between iCBCT scans was measured. Uniform expansions were applied to the planning CTV to assess target coverage. RESULTS: The motion (mean ± standard deviation) in the CTV-U position was 8.3 ± 4.1 mm in the left, 9.8 ± 4.4 mm in the right, 12.6 ± 4.0 mm in the anterior, 8.8 ± 5.1 mm in the posterior, 5.7 ± 5.4 mm in the superior, and 3.0 ± 3.2 mm in the inferior direction. The mean CTV-C displacement was 7.3 ± 3.2 mm in the left, 8.6 ± 3.8 mm in the right, 9.0 ± 6.1 mm in the anterior, 8.4 ± 3.6 mm in the posterior, 5.0 ± 5.0 mm in the superior, and 3.0 ± 2.5 mm in the inferior direction. Compared with the other tumor (T) stages, CTV-U and CTV-C motion in stage T1 was larger. A uniform CTV planning treatment volume margin of 15 mm failed to encompass the CTV-U and CTV-C in 11.1% and 2.2% of all fractions, respectively. The mean volume change of CTV-U and CTV-C were 150% and 51%, respectively, compared with the planning CTV. CONCLUSIONS: Movements of the uterine corpus are larger than those of the cervix. The likelihood of missing the CTV is significantly increased due to inter-fractional motion when utilizing traditional planning margins. Early T stage may require larger margins. Personal radiotherapy margining is needed to improve treatment accuracy.

Outbreak of NDM-5-producing Klebsiella pneumoniae ST307: an emerging high-risk antimicrobial resistance clone in Shanghai, China.

The high-risk clone Klebsiella pneumoniae ST307, associated with various carbapenem resistance genes, exhibits a global distribution and prevalence. However, in China, it has remained sporadic and has rarely been detected. In this study, we reported an outbreak caused by nine ST307 CRKP isolates harboring blaNDM-5 in Shanghai, China, in 2022. We employed antimicrobial susceptibility testing, conjugation assay, whole-genome sequencing (WGS) and comparative genomics, phylogenetic analysis, and fitness and virulence comparison to further characterize the isolates causing the outbreak. Besides blaNDM-5, these nine isolates co-carried blaCTX-M-15 and blaDHA-1, exhibiting nearly identical resistance profiles with high-level resistance to carbapenems and ceftazidime/avibactam, while showing susceptibility to colistin and tigecycline. blaNDM-5 was located on an IncX3 plasmid of 45,403 bp with a high frequency of conjugative ability. Phylogenetic and single-nucleotide polymorphism (SNP) analysis indicated the nature of clonal transmission with a maximum of five SNPs between these nine isolates, and they were closely related to strains obtained from the United States. ST307 isolates in our study showed a relatively lower virulence but higher growth rates and certain adaptability compared with ST11 isolates. Clinical investigation revealed that shared nursing staff in a mixed emergency intensive care unit ward and doctors' movement between wards might be responsible for the outbreak. The nonexistence before and sudden emergence of ST307 suggested that the currently circulating ST307 clone was a newly introduced superbug in our hospital. In conclusion, we revealed that blaNDM-5-producing ST307 CRKP isolates, a globally significant high-risk clone, are spreading in China, posing a substantial threat to public health.IMPORTANCEThe high-risk clone ST307, associated with various carbapenemases, including KPC, NDM, and OXA, has a global distribution. However, it is rarely reported in China, let alone causing outbreaks. Here, we found an outbreak caused by the clonal transmission of nine ST307 CRKP isolates. Clinical investigation revealed that shared nurses in a mixed emergency intensive care unit ward and doctors' movement between wards might be responsible for the outbreak. In our study, the nine NDM-5-producing ST307 isolates exhibited high-level resistance to carbapenems and ceftazidime-avibactam, high conjugative ability to Escherichia coli J53, and certain adaptability to environment, phylogenetically closet to the United States. All these features make ST307 clone the next successful clone comparable to ST11 clone in China. Therefore, it is imperative for us to vigilantly monitor the prevalence of carbapenem-resistant Klebsiella pneumoniae and promptly implement measures to control the spread of K. pneumoniae ST307 in China.

The first pineoblastoma case report of a patient with Sotos syndrome harboring NSD1 germline mutation.

Germline mutations of NSD1 are associated with Sotos syndrome, characterized by distinctive facial features, overgrowth, and developmental delay. Approximately 3% of individuals with Sotos syndrome develop tumors. In this study, we describe an infant in pineoblastoma with facial anomalies, learning disability and mild autism at 1 years diagnosed as Sotos syndrome owing to carrying a novel mutation de novo germline NSD1 likely pathogenic variant. This patient expands both the mutation and phenotype spectrum of the Sotos Syndrome and provides new clinical insights into the potential mechanism of underlying pinealoblastoma pathology.

Preoperative glucose-to-lymphocyte ratio predicts survival in cancer.

Background: Systemic inflammation and glucose metabolism have been closely related to the survival of cancer patients. Therefore, we aimed to evaluate whether preoperative glucose-to-lymphocyte ratio (GLR) can be used to predict the survival of cancer patients. Methods: We retrospectively examined 2172 cancer patients who underwent surgery from January 1, 2014, to December 31, 2016. There were 240 patients with non-small cell lung cancer (NSCLC), 378 patients with colorectal cancer (CRC), 221 patients with breast cancer (BC), 335 patients with gastric cancer (GC), 270 patients with liver cancer, 233 patients with esophageal cancer (EC), 295 patients with renal cancer, and 200 patients with melanoma. The formula for preoperative GLR calculation was as follows: GLR=glucose/lymphocyte count. The overall survival (OS) was estimated using the Kaplan-Meier method. The predictive factors for OS were determined using multivariate analysis. Results: The Kaplan-Meier analysis showed that the median survival time in the high-GLR group was much shorter than that of those in the low-GLR group for different cancers. Cox multivariate regression analysis reveals that preoperative GLR was an independent factor for predicting overall survival in different tumor types. Conclusion: Elevated preoperative GLR was remarkably associated with a poorer prognosis in patients with NSCLC, CRC, breast cancer, gastric cancer, kidney cancer, liver cancer, esophageal cancer, and melanoma. Preoperative GLR promises to be an essential predictor of survival for cancer patients.

Release of biogenic volatile organic compounds and physiological responses of two sub-tropical tree species to smoke derived from forest fire.

Forests emit a large amount of biogenic volatile organic compounds (BVOCs) in response to biotic and abiotic stress. Despite frequent occurrence of large forest fires in recent years, the impact of smoke stress derived from these forest fires on the emission of BVOCs is largely unexplored. Thus, the aims of the study were to quantify the amount and composition of BVOCs released by two sub-tropical tree species, Cunninghamia lanceolata and Schima superba, in response to exposure to smoke. Physiological responses and their relationship with BVOCs were also investigated. The results showed that smoke treatments significantly (p < 0.001) promoted short-term release of BVOCs by C. lanceolata leaves than S. superba; and alkanes, olefins and benzene homologs were identified as major classes of BVOCs. Both C. lanceolata and S. superba seedlings showed significant (p < 0.005) physiological responses after being smoke-stressed where photosynthetic rate remained unaffected, chlorophyll content greatly reduced and Activities of anti-oxidant enzymes and the malondialdehyde content generally increased with the increase in smoke concentration. Activities of anti-oxidant enzymes showed mainly positive correlations with the major BVOCs. In conclusion, the release of BVOCs following smoke stress is species-specific and there exists a link between activities of antioxidant enzymes and BVOCs released. The findings provide insight about management of forest fires in order to control excessive emission of smoke that would trigger increased release of BVOCs.

NiCo2 O4 Nanowires Immobilized on Nitrogen-Doped Ti3 C2 Tx for High-Performance Wearable Magnesium-Air Batteries.

Flexible magnesium (Mg)-air batteries provide an ideal platform for developing efficient energy-storage devices toward wearable electronics and bio-integrated power sources. However, high-capacity bio-adaptable Mg-air batteries still face the challenges in low discharge potential and inefficient oxygen electrodes, with poor kinetics property toward oxygen reduction reaction (ORR). Herein, spinel nickel cobalt oxides (NiCo2 O4 ) nanowires immobilized on nitrogen-doped Ti3 C2 Tx (NiCo2 O4 /N-Ti3 C2 Tx ) are reported via surface chemical-bonded effect as oxygen electrodes, wherein surface-doped pyridinic-N-C and Co-pyridinic-N moieties accounted for efficient ORR owing to increased interlayer spacing and changed surrounding environment around Co metals in NiCo2 O4 . Importantly, in polyethylene glycol (PVA)-NaCl neutral gel electrolytes, the NiCo2 O4 /N-Ti3 C2 Tx -assembled quasi-solid wearable Mg-air batteries delivered high open-circuit potential of 1.5 V, good flexibility under various bent angles, high power density of 9.8 mW cm-2 , and stable discharge duration to 12 h without obvious voltage drop at 5 mA cm-2 , which can power a blue flexible light-emitting diode (LED) array and red smart rollable wearable device. The present study stimulates studies to investigate Mg-air batteries involving human-body adaptable neutral electrolytes, which will facilitate the application of Mg-air batteries in portable, flexible, and wearable power sources for electronic devices.

Exploiting bacterial-origin immunostimulants for improved vaccination and immunotherapy: current insights and future directions.

Vaccination is a valid strategy to prevent and control newly emerging and reemerging infectious diseases in humans and animals. However, synthetic and recombinant antigens are poor immunogenic to stimulate efficient and protective host immune response. Immunostimulants are indispensable factors of vaccines, which can promote to trigger fast, robust, and long-lasting immune responses. Importantly, immunotherapy with immunostimulants is increasing proved to be an effective and promising treatment of cancer, which could enhance the function of the immune system against tumor cells. Pattern recognition receptors (PRRs) play vital roles in inflammation and are central to innate and adaptive immune responses. Toll-like receptors (TLRs)-targeting immunostimulants have become one of the hotspots in adjuvant research and cancer therapy. Bacterial-origin immunoreactive molecules are usually the ligands of PRRs, which could be fast recognized by PRRs and activate immune response to eliminate pathogens. Varieties of bacterial immunoreactive molecules and bacterial component-mimicking molecules have been successfully used in vaccines and clinical therapy so far. This work provides a comprehensive review of the development, current state, mechanisms, and applications of bacterial-origin immunostimulants. The exploration of bacterial immunoreactive molecules, along with their corresponding mechanisms, holds immense significance in deepening our understanding of bacterial pathogenicity and in the development of promising immunostimulants.