Removal of particulate matter and dissolved organic matter from sedimentation sludge water during pre-sedimentation process: Performances and mechanisms.

Sedimentation sludge water (SSW), a prominent constituent of wastewater from drinking water treatment plants, has received limited attention in terms of its treatment and utilization likely due to the perceived difficulties associated with managing SSW sludge. This study comprehensively evaluated the water quality of SSW by comparing it to a well-documented wastewater (filter backwash water (FBW)). Furthermore, it investigated the pollutant variations in the SSW during pre-sedimentation process, probed the underlying reaction mechanism, and explored the feasibility of employing a pilot-scale coagulation-sedimentation process for SSW treatment. The levels of most water quality parameters were generally comparable between SSW and FBW. During the pre-sedimentation of SSW, significant removal of turbidity, bacterial counts, and dissolved organic matter (DOM) was observed. The characterization of DOM components, molecular weight distributions, and optical properties revealed that the macromolecular proteinaceous biopolymers and humic acids were preferentially removed. The characterization of particulates indicated that high surface energy, zeta potential, and bridging/adsorption/sedimentation/coagulation capacities in aluminum residuals of SSW, underscoring its potential as a coagulant and promoting the generation and sedimentation of inorganic-organic complexes. The coagulation-sedimentation process could effectively remove pollutants from low-turbidity SSW ([turbidity]0 < 15 NTU). These findings provide valuable insights into the water quality dynamics of SSW during the pre-sedimentation process, facilitating the development of SSW quality management and enhancing its reuse rate.

Removal of benzo[a]pyrene from the soil by adsorption coupled with degradation on saponin-modified bentonite immobilized crude enzymes.

Bentonite is a non-metallic mineral with montmorillonite as the main component. It is an environmentally friendly mineral material with large reserves, wide distribution, and low price. Bentonite can be easily modified organically using the surfactant saponin to obtain saponin-modified bentonite (Sap-BT). This study investigates the immobilization of crude enzymes obtained from Trametes versicolor by physical adsorption with Sap-BT. Thus, saponin-modified bentonite immobilized crude enzymes (CE-Sap-BT) were developed to remove benzo[a]pyrene. Immobilization improves the stability of free enzymes. CE-Sap-BT can maintain more than 80% of activity at 45°C and after storage for 15 d. Additionally, CE-Sap-BT exhibited a high removal rate of benzo[a]pyrene in soil, with 65.69% after 7 d in highly contaminated allotment soil and 52.90% after 6 d in actual soil contaminated with a low concentration of benzo[a]pyrene at a very low laccase dosage (0.1 U/3 g soil). The high catalytic and removal performance of CE-Sap-BT in contaminated sites showed more excellent practical application value.

Benefits From Different Modes of Slow and Deep Breathing on Vagal Modulation.

Slow and deep breathing (SDB) is a relaxation technique that can increase vagal activity. Respiratory sinus arrhythmia (RSA) serves as an index of vagal function usually quantified by the high-frequency power of heart rate variability (HRV). However, the low breathing rate during SDB results in deviations when estimating RSA by HRV. Besides, the impact of the inspiration-expiration (I: E) ratio and guidelines ways (fixed breathing rate or intelligent guidance) on SDB is not yet clear. In our study, 30 healthy people (mean age = 26.5 years, 17 females) participated in three SDB modes, including 6 breaths per minute (bpm) with an I:E ratio of 1:1/ 1:2, and intelligent guidance mode (I:E ratio of 1:2 with guiding to gradually lower breathing rate to 6 bpm). Parameters derived from HRV, multimodal coupling analysis (MMCA), Poincaré plot, and detrended fluctuation analysis were introduced to examine the effects of SDB exercises. Besides, multiple machine learning methods were applied to classify breathing patterns (spontaneous breathing vs. SDB) after feature selection by max-relevance and min-redundancy. All vagal-activity markers, especially MMCA-derived RSA, statistically increased during SDB. Among all SDB modes, breathing at 6 bpm with a 1:1 I:E ratio activated the vagal function the most statistically, while the intelligent guidance mode had more indicators that still significantly increased after training, including SDRR and MMCA-derived RSA, etc. About the classification of breathing patterns, the Naive Bayes classifier has the highest accuracy (92.2%) with input features including LFn, CPercent, pNN50, [Formula: see text], SDRatio, [Formula: see text], and LF. Our study proposed a system that can be applied to medical devices for automatic SDB identification and real-time feedback on the training effect. We demonstrated that breathing at 6 bpm with an I:E ratio of 1:1 performed best during the training phase, while intelligent guidance mode had a more long-lasting effect.

Synthesis and Evaluation of Novel meso-Tetraphenyltetrabenzoporphyrins for Photodynamic Therapy.

To discover effective photosensitizers for photodynamic therapy (PDT), a series of new meso-tetraphenyltetrabenzoporphyrin (m-Ph4TBP) derivatives were designed, prepared, and characterized. All m-Ph4TBPs own two characteristic absorption bands in the range of 450-500 and 600-700 nm and have the ability to generate singlet oxygen upon photoexcitation. Most of the m-Ph4TBPs demonstrated high photoactivity, among which compounds I4, I6, I12, and I13 induced apoptosis and also exhibited excellent photodynamic activities in vivo. Nonetheless, the liver organs of the I4 and I6-PDT groups showed clear calcifications, whereas the liver tissues of the other PDT groups showed no calcification. It was indicated that compared to phenolic m-Ph4TBPs, glycol m-Ph4TBPs exhibited superior biological safety in mice. According to comprehensive evaluations, m-Ph4TBP I12 displayed excellent photodynamic antitumor efficacy and biological safety and can be regarded as a promising antitumor drug candidate.

Data-Driven and Machine Learning to Screen Metal-Organic Frameworks for the Efficient Separation of Methane.

With the rapid growth of the economy, people are increasingly reliant on energy sources. However, in recent years, the energy crisis has gradually intensified. As a clean energy source, methane has garnered widespread attention for its development and utilization. This study employed both large-scale computational screening and machine learning to investigate the adsorption and diffusion properties of thousands of metal-organic frameworks (MOFs) in six gas binary mixtures of CH4 (H2/CH4, N2/CH4, O2/CH4, CO2/CH4, H2S/CH4, He/CH4) for methane purification. Firstly, a univariate analysis was conducted to discuss the relationships between the performance indicators of adsorbents and their characteristic descriptors. Subsequently, four machine learning methods were utilized to predict the diffusivity/selectivity of gas, with the light gradient boosting machine (LGBM) algorithm emerging as the optimal one, yielding R2 values of 0.954 for the diffusivity and 0.931 for the selectivity. Furthermore, the LGBM algorithm was combined with the SHapley Additive exPlanation (SHAP) technique to quantitatively analyze the relative importance of each MOF descriptor, revealing that the pore limiting diameter (PLD) was the most critical structural descriptor affecting molecular diffusivity. Finally, for each system of CH4 mixture, three high-performance MOFs were identified, and the commonalities among high-performance MOFs were analyzed, leading to the proposals of three design principles involving changes only to the metal centers, organic linkers, or topological structures. Thus, this work reveals microscopic insights into the separation mechanisms of CH4 from different binary mixtures in MOFs.

Vancomycin-Loaded Sol-Gel System for In Situ Coating of Artificial Bone to Prevent Surgical Site Infections.

Surgical site infections (SSIs) related to implants have always been a major challenge for clinical doctors and patients. Clinically, doctors may directly apply antibiotics into the wound to prevent SSIs. However, this strategy is strongly associated with experience of doctors on the amount and the location of antibiotics. Herein, an in situ constructable sol-gel system is developed containing antibiotics during surgical process and validated the efficacy against SSIs in beagles. The system involves chitosan (CS), ß-glycerophosphate (ß-GP) and vancomycin (VAN), which can be adsorbed onto porous hydroxyapatite (HA) and form VAN-CS/ß-GP@HA hydrogel in a short time. The VAN concentration from VAN-CS/ß-GP@HA hydrogel is higher than minimum inhibitory concentration (MIC) against Staphylococcus aureus (S. aureus) at the 21st day in vitro. In an in vivo canine model for the prevention of SSIs in the femoral condyle, VAN-CS/ß-GP@HA exhibits excellent biocompatibility, antimicrobial properties, and promotion of bone healing. In all, the CS/ß-GP instant sol-gel system is able to in situ encapsulate antibiotics and adhere on artificial bone implants during the surgery, effectively preventing SSIs related to implants.

Multiple effects of spicy flavors on neurological diseases through the intervention of TRPV1: a critical review.

The spicy properties of foods are contributed by various spicy flavor substances (SFs) such as capsaicin, piperine, and allicin. Beyond their distinctive sensory characteristics, SFs also influence health conditions and numerous studies have associated spicy flavors with disease treatment. In this review, we enumerate different types of SFs and describe their role in food processing, with a specific emphasis on critically examining their influence on human wellness. Particularly, detailed insights into the mechanisms through which SFs enhance physiological balance and alleviate neurological diseases are provided, and a systematic analysis of the significance of transient receptor potential vanilloid type-1 (TRPV1) in regulating metabolism and nervous system homeostasis is presented. Moreover, enhancing the accessibility and utilization of SFs can potentially amplify the physiological effects. This review aims to provide compelling evidence for the integration of food flavor and human health.

Equisetin protects from atherosclerosis in vivo by binding to STAT3 and inhibiting its activity.

Atherosclerosis is a chronic inflammatory vascular disease characterized by lipid metabolism disorder and lipid accumulation. Equisetin (EQST) is a hemiterpene compound isolated from fungus of marine sponge origin, which has antibacterial, anti-inflammatory, lipid-lowering, and weight loss effects. Whether EQST has anti-atherosclerotic activity has not been reported. In this study, we revealed that EQST displayed anti- atherosclerosis effects through inhibiting macrophage inflammatory response, lipid uptake and foam cell formation in vitro, and finally ameliorated high-fat diet (HFD)-induced atherosclerosis in AopE-/- mice in vivo. Mechanistically, EQST directly bound to STAT3 with high-affinity by forming hydrophobic bonds at GLN247 and GLN326 residues, as well as hydrogen bonds at ARG325 and THR346 residues. EQST interacted with STAT3 physically, and functionally inhibited the transcription activity of STAT3, thereby regulating atherosclerosis. Therefore, these results supports EQST as a candidate for developing anti-atherosclerosis therapeutic agent.

Shallow sea reverberation suppression based on a range azimuth patch matrix model.

Reverberation is the main background interference for active sonar detection in shallow sea. Reverberation suppression is crucial for enhancing the performance of active sonar. In this paper, a reverberation suppression method based on low-rank sparse decomposition is proposed. First, both the sparseness property of the targets and the non-local self-correlation property of the reverberation are used to construct a range azimuth patch matrix model. The reverberation suppression problem is then transformed into an optimization problem for the recovery of a low-rank sparse matrix. The validity of the proposed method is verified by using the measured data. Results show that, compared with the reverberation pre-whitening and sparse fractional Fourier transform methods, the proposed method significantly improves the reverberation suppression performance and achieves a better detection result when the signal-to-interference ratio is below -2 dB.

Biomarker Testing Disparities in Metastatic Colorectal Cancer.

Importance: Among patients with metastatic colorectal cancer (mCRC), data are limited on disparate biomarker testing and its association with clinical outcomes on a national scale. Objective: To evaluate the socioeconomic and demographic inequities in microsatellite instability (MSI) and KRAS biomarker testing among patients with mCRC and to explore the association of testing with overall survival (OS). Design, Setting, and Participants: This cohort study, conducted between November 2022 and March 2024, included patients who were diagnosed with mCRC between January 1, 2010, and December 31, 2017. The study obtained data from the National Cancer Database, a hospital-based cancer registry in the US. Patients with mCRC and available information on biomarker testing were included. Patients were classified based on whether they completed or did not complete MSI or KRAS tests. Exposure: Demographic and socioeconomic factors, such as age, race, ethnicity, educational level in area of residence, median household income, insurance type, area of residence, facility type, and facility location were evaluated. Main Outcomes and Measures: The main outcomes were MSI and KRAS testing between the date of diagnosis and the date of first-course therapy. Univariable and multivariable logistic regressions were used to identify the relevant factors in MSI and KRAS testing. The OS outcomes were also evaluated. Results: Among the 41 061 patients included (22 362 males [54.5%]; mean [SD] age, 62.3 [10.1] years; 17.3% identified as Black individuals, 78.0% as White individuals, 4.7% as individuals of other race, with 6.5% Hispanic or 93.5% non-Hispanic ethnicity), 28.8% underwent KRAS testing and 43.7% received MSI testing. A significant proportion of patients had Medicare insurance (43.6%), received treatment at a comprehensive community cancer program (40.5%), and lived in an area with lower educational level (51.3%). Factors associated with a lower likelihood of MSI testing included age of 70 to 79 years (relative risk [RR], 0.70; 95% CI, 0.66-0.74; P < .001), treatment at a community cancer program (RR, 0.74; 95% CI, 0.70-0.79; P < .001), rural residency (RR, 0.80; 95% CI, 0.69-0.92; P < .001), lower educational level in area of residence (RR, 0.84; 95% CI, 0.79-0.89; P < .001), and treatment at East South Central facilities (RR, 0.67; 95% CI, 0.61-0.73; P < .001). Similar patterns were observed for KRAS testing. Survival analysis showed modest OS improvement in patients with MSI testing (hazard ratio, 0.93; 95% CI, 0.91-0.96; P < .001). The median (IQR) follow-up time for the survival analysis was 13.96 (3.71-29.34) months. Conclusions and Relevance: This cohort study of patients with mCRC found that older age, community-setting treatment, lower educational level in area of residence, and treatment at East South Central facilities were associated with a reduced likelihood of MSI and KRAS testing. Highlighting the sociodemographic-based disparities in biomarker testing can inform the development of strategies that promote equity in cancer care and improve outcomes for underserved populations.

Assessment of metabolomic variations among individuals returning to plain areas after exposure to high altitudes: a metabolomic analysis of human plasma samples with high-altitude de-acclimatization syndrome.

Background: High altitude de-acclimatization (HADA) is gradually becoming a public health concern as millions of individuals of different occupations migrate to high-altitude areas for work due to economic growth in plateau areas. HADA affects people who return to lower elevations after exposure to high altitudes. It causes significant physiological and functional changes that can negatively impact health and even endanger life. However, uncertainties persist about the detailed mechanisms underlying HADA. Methods: We established a population cohort of individuals with HADA and assessed variations in metabolite composition. Plasm samples of four groups, including subjects staying at plain (P) and high altitude (H) as well as subjects suffering from HADA syndrome with almost no reaction (r3) and mild-to-moderate reaction (R3) after returning to plain from high altitude, were collected and analyzed by Liquid Chromatography-Mass Spectrometry metabolomic. Multivariate statistical analyses were used to explore significant differences and potential clinical prospect of metabolites. Result: Although significantly different on current HADAS diagnostic symptom score, there were no differences in 17 usual clinical indices between r3 and R3. Further multivariate analyses showed isolated clustering distribution of the metabolites among the four groups, suggesting significant differences in their metabolic characteristics. Through K-means clustering analysis, we identified 235 metabolites that exhibited patterns of abundance change consistent with phenotype of HADA syndrome. Pathway enrichment analysis indicated a high influence of polyunsaturated fatty acids under high-altitude conditions. We compared the metabolites between R3 and r3 and found 107 metabolites with differential abundance involved in lipid metabolism and oxidation, suggesting their potential role in the regulation of oxidative stress homeostasis. Among them, four metabolites might play a key role in the occurrence of HADA, including 11-beta-hydroxyandrosterone-3-glucuronide, 5-methoxyindoleacetate, 9,10-epoxyoctadecenoic acid, and PysoPC (20:5). Conclusion: We observed the dynamic variation in the metabolic process of HADA. Levels of four metabolites, which might be provoking HADA mediated through lipid metabolism and oxidation, were expected to be explore prospective indices for HADA. Additionally, metabolomics was more efficient in identifying environmental risk factors than clinical examination when dramatic metabolic disturbances underlying the difference in symptoms were detected, providing new insights into the molecular mechanisms of HADAS.

Development and validation of machine learning models to predict MDRO colonization or infection on ICU admission by using electronic health record data.

BACKGROUND: Multidrug-resistant organisms (MDRO) pose a significant threat to public health. Intensive Care Units (ICU), characterized by the extensive use of antimicrobial agents and a high prevalence of bacterial resistance, are hotspots for MDRO proliferation. Timely identification of patients at high risk for MDRO can aid in curbing transmission, enhancing patient outcomes, and maintaining the cleanliness of the ICU environment. This study focused on developing a machine learning (ML) model to identify patients at risk of MDRO during the initial phase of their ICU stay. METHODS: Utilizing patient data from the First Medical Center of the People's Liberation Army General Hospital (PLAGH-ICU) and the Medical Information Mart for Intensive Care (MIMIC-IV), the study analyzed variables within 24 h of ICU admission. Machine learning algorithms were applied to these datasets, emphasizing the early detection of MDRO colonization or infection. Model efficacy was evaluated by the area under the receiver operating characteristics curve (AUROC), alongside internal and external validation sets. RESULTS: The study evaluated 3,536 patients in PLAGH-ICU and 34,923 in MIMIC-IV, revealing MDRO prevalence of 11.96% and 8.81%, respectively. Significant differences in ICU and hospital stays, along with mortality rates, were observed between MDRO positive and negative patients. In the temporal validation, the PLAGH-ICU model achieved an AUROC of 0.786 [0.748, 0.825], while the MIMIC-IV model reached 0.744 [0.723, 0.766]. External validation demonstrated reduced model performance across different datasets. Key predictors included biochemical markers and the duration of pre-ICU hospital stay. CONCLUSIONS: The ML models developed in this study demonstrated their capability in early identification of MDRO risks in ICU patients. Continuous refinement and validation in varied clinical contexts remain essential for future applications.

Disruption of zebrafish sex differentiation by emerging contaminants hexafluoropropylene oxides at environmental concentrations via antagonizing androgen receptor pathways.

As alternatives of perfluorooctanoic acid (PFOA), hexafluoropropylene oxide dimeric acid (HFPO-DA) and trimeric acid (HFPO-TA) have been detected increasingly in environmental media and even humans. They have been shown to exhibit reproductive toxicity to model species, but their effects on human remain unclear due to the knowledge gap in their mode of action. Herein, (anti-)androgenic effects of the two HFPOs and PFOA were investigated and underlying toxicological mechanism was explored by combining zebrafish test, cell assay and molecular docking simulation. Exposure of juvenile zebrafish to the chemicals during sex differentiation promoted feminization, with HFPO-TA acting at an environmental concentration of 1 µg/L. The chemicals inhibited proliferation of human prostate cells and transcriptional activity of human and zebrafish androgen receptors (AR), with HFPO-TA displaying the strongest potency. Molecular docking revealed that the chemicals bind to AR in a conformation similar to a known AR antagonist. Combined in vivo, in vitro and in silico results demonstrated that the chemicals disrupted sex differentiation likely by antagonizing AR-mediated pathways, and provided more evidence that HFPO-TA is not a safe alternative to PFOA.

Enhanced biodegradation of benzo[a]pyrene with Trametes versicolor stimulated by citric acid.

Polycyclic aromatic hydrocarbons (PAHs) are a class of persistent organic pollutants with carcinogenic, mutagenic and teratogenic effects. The white-rot fungi in the fungal group have significant degradation ability for high molecular weight organic pollutants. However, exogenous fungi are easily antagonized by indigenous microorganisms. Low molecular weight organic acids, a small molecular organic matter secreted by plants, can provide carbon sources for soil microorganisms. Combining organic acids with white rot fungi may improve the nutritional environment of fungi. In this study, immobilized Trametes versicolor was used to degrade benzo[a]pyrene in soil, and its effect on removing benzo[a]pyrene in soil mediated by different low molecular weight organic acids was investigated. The results showed that when the degradation was 35 days, the removal effect of the experimental group with citric acid was the best, reaching 43.7%. The degradation effect of Trametes versicolor on benzo[a]pyrene was further investigated in the liquid medium when citric acid was added, and the effects of citric acid on the biomass, extracellular protein concentration and laccase activity of Trametes versicolor were investigated by controlling different concentrations of citric acid. In general, citric acid can act as a carbon source for Trametes versicolor and promote its extracellular protein secretion and laccase activity, thereby accelerating the mineralization of benzo[a]pyrene by Trametes versicolor. Therefore, citric acid can be used as a biostimulant in the remediation of PAHs contaminated soil with Trametes versicolor.

Laparoscopic versus robotic-assisted primary bariatric-metabolic surgery. Are we still expecting to overcome the learning curve? A propensity score-matched analysis of the Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program database.

BACKGROUND: Robotic surgery is becoming increasingly popular in bariatric-metabolic surgery. However, its superiority regarding postoperative outcomes compared with conventional laparoscopy has not been clearly proven. With growing adoption of robotic surgery and improved technologies, benefits should become more evident. OBJECTIVES: Evaluate readmission and reoperation rates after bariatric-metabolic surgery performed by conventional laparoscopy versus robotic-assisted from 2015 to 2021. SETTING: Academic institution. METHODS: The Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program (MBSAQIP) was reviewed for primary bariatric operations performed with conventional laparoscopy versus robotic-assisted. Postoperative outcomes were compared in a propensity score-matched sample. RESULTS: Of 1,059,348 cases meeting inclusion criteria, 921,322 (87%) were conventional laparoscopic bariatric-metabolic surgeries, which were matched 1:1 with robotic-assisted cases (138,026). Reoperation (odds ratio [OR] 1.07; 95% confidence interval [CI] 1.00-1.15, P = .0463), postoperative morbidity (OR 1.07; 95% CI 1.01-1.12, P = .0193), readmission (OR 1.14; 95% CI 1.09-1.18, P < .0001), and emergency department visits (OR 1.06; 95% CI 1.03-1.09, P = .0003) at 30 days postoperatively were significantly greater for robotic-assisted cases. Robotic-assisted cases had a similar mortality rate at 30 days postoperatively and length of stay >3 days when compared with conventional laparoscopic cases. Similar results were observed in cases from 2020 to 2021, except for reoperation and emergency department visits, which showed no difference between groups and length of stay >3 days, which was greater in robotic-assisted cases. CONCLUSIONS: Our results show a greater readmission and reoperation rate and greater morbidity at 30 days postoperatively in robotic-assisted bariatric-metabolic surgery compared with conventional laparoscopy. Analyzing only cases performed between 2020 and 2021, robotic surgery also does not show superiority over conventional laparoscopy.

Gestational organophosphate esters (OPEs) exposure in association with placental DNA methylation levels of peroxisome proliferator-activated receptors (PPARs) signaling pathway-related genes.

BACKGROUND: Organophosphate esters (OPEs) exposure could affect offspring health. However, the underlying mechanisms are not well documented. OBJECTIVES: Based on a birth cohort study, we aimed to investigate the associations among gestational OPEs exposure, placental DNA methylation levels of peroxisome proliferator-activated receptor (PPAR) signaling pathway-related genes, and fetal growth. METHODS: We measured the concentrations of eight OPE metabolites in maternal urine samples and neonatal anthropometric measurements in 733 mother-child pairs. In 327 placental samples, we assessed the DNA methylation levels of 14 genes which were involved in the PPARs signaling pathway and expressed in placenta. Multiple linear regression models were used to examine the associations of OPEs exposure with placental DNA methylation, and of OPEs and placental DNA methylation with neonatal anthropometric measurements. Causal mediation analyses were conducted to examine the potential mediating role of placental DNA methylation in the pathway between OPEs exposure and fetal growth. RESULTS: We observed a general pattern of OPEs exposure being associated with hypermethylation of candidate genes, with statistically significant associations identified for several OPEs with RXRA, ACAA1, ACADL, ACADM, PLTP, and NR1H3 methylation. Further, gestational exposure to BCIPP, DPP, BBOEP, ∑NCl-OPEs, and ∑OPEs tended to be associated with lower anthropometric measurements, with more significant associations observed on arm circumference, and abdominal and back skinfold thickness. Notably, RXRA, ACAA1, ACOX1, CPT2, ACADM, and NR1H3 methylation tended to be associated with lower neonatal anthropometric measurements, especially for abdominal and back skinfold thickness. Moreover, mediation analyses showed that 19.42 % of the total effect of DPP on the back skinfold thickness was mediated by changes in RXRA methylation, and there was a significant indirect effect of RXRA methylation. CONCLUSIONS: Gestational OPEs exposure could disrupt the placental DNA methylation levels of PPAR signaling pathway-related genes, which might contribute to the effect of OPEs on fetal growth.

Enhance PD/A biofilm formation via a novel biochar/tourmaline modified-biocarriers to treat low-strength contaminated surface water: Initial adhesion and high-substrate microenvironment.

In this work, a novel polyurethane carrier modified with biochar and tourmaline/zeolite powder at ratio of 1:1 and 1:2 was developed to promote the formation of biofilms and the synergy of overall bacterial activity for Partial Denitrification/Anammox to treat low-nitrogen contaminated surface water. Based on the batch experiment, the modified biocarrier, BTP2 (biochar: tourmaline = 2: 1), exhibited the highest total nitrogen removal efficiency (83.63%) under influent total nitrogen of 15 mg/L and COD/NO3- of 3. The dense biofilm was formed in inner side of biocarrier owing to the increased surface roughness and various functional groups suggested by scanning electron microscopy and Fourier-transform infrared analysis. The EPS content increased from 200.15 to 220.26 mg/g VSS in BTP2 system. Besides, the rapid NH4+ capture and organics release of the modified carrier fueled the growth of anammox and denitrification bacteria, with the activity of 2.13 ± 0.52 mg N/gVSS/h and 6.70 ± 0.52 mg N/gVSS/h (BTP2). High-throughput sequencing unraveled the increased abundances of Candidatus_Competibacter (0.82%), Thauera (0.60%) and Candidatus_Brocadia (0.55%) which was responsible for the synergy of incomplete reduction of NO3- to NO2- and NH4+ oxidation. Overall, this study provided a valid and simple-control guide for biofilm formation towards rapid enrichment and great collaboration of Anammox and denitrification bacteria.

Insights into the antineoplastic activity and mechanisms of action of coumarin-coordinated 8-hydroxyquinoline ruthenium(II/III) compounds.

Ruthenium(II/III) coordination compounds have gained widespread attention as chemotherapy drugs, photosensitizers, and photodynamic therapy reagents. Herein, a family of 11 novel coumarin-coordinated 8-hydroxyquinoline ruthenium(II/III) compounds, i.e., [RuII2(µ2-Cl)2(QL1a)2(DMSO)4] (YNU-4a = Yulin Normal University-4a), [RuII2(µ2-Cl)2(QL1b)2(DMSO)4] (YNU-4b), [RuII2(µ2-Cl)2(QL1c)2(DMSO)4] (YNU-4c), [RuII2(µ2-Cl)2(QL1d)2(DMSO)4]⋅2CH3OH (YNU-4d), [RuII(QL1e)2(DMSO)2] (YNU-4e), [RuIII(QL1e)2(QL3a)] (YNU-4f), [RuIII(QL1e)2(QL3b)] (YNU-4g), [RuIII(QL1e)2(QL3c)] (YNU-4h), [RuIICl2(H-QL3a)2(DMSO)2] (YNU-4i), [RuIICl2(H-QL3b)2(DMSO)2] (YNU-4j), and [RuIICl2(H-QL3c)2(DMSO)2] (YNU-4k), featuring the coligands 5,7-diiodo-8-hydroxyquinoline (H-QL1a), 5,7-dichloro-8-quinolinol (H-QL1b), 5-chloro-7-iodo-8-hydroxyquinolin (H-QL1c), 5,7-dibromo-8-hydroxyquinoline (H-QL1d), and 5,7-dichloro-8-hydroxy-2-methylquinoline (H-QL1e) and the main ligands 6,7-dichloro-3-pyridin-2-yl-chromen-2-one (H-QL3a), 6-bromo-3-pyridin-2-yl-chromen-2-one (H-QL3b), and 6-chloro-3-pyridin-2-yl-chromen-2-one (H-QL3c), respectively. The structure of compounds YNU-4a-YNU-4k was fully confirmed by conducting various spectroscopic analyses. The anticancer activity of YNU-4a-YNU-4k was evaluated in cisplatin-resistant A549/DDP lung cancer cells (LC549) versus normal embryonic kidney (HEK293) cells. Notably, compound YNU-4f bearing QL1e and QL3a ligands showed a more pronounced antiproliferative effect against LC549 cells (IC50 = 1.75 ± 0.09 µM) with high intrinsic selectivity toward LC549 cancer cells than YNU-4a-YNU-4e, H-QL1a-H-QL1e, cisplatin (PDD), YNU-4g-YNU-4k, and H-QL3a-H-QL3c. Additionally, a colocalization assay analysis of YNU-4e and YNU-4f showed that these two ruthenium(II/III) compounds were subcellularly accumulated in the mitochondria and other regions of the cytoplasm, where they induce mitophagy, adenosine triphosphate (ATP) reduction, mitochondrial respiratory chain complex I/IV(RC1/RC4) inhibition, and mitochondrial dysfunction. Accordingly, compounds YNU-4a-YNU-4k can be regarded as mitophagy inductors for the eradication of cisplatin-resistant LC549 cancer cells.

Molecular fingerprint and machine learning enhance high-performance MOFs for mustard gas removal.

Chemical warfare agents (CWAs), epitomized by the notoriously used mustard gas (HD), represent a class of exceptionally toxic chemicals whose airborne removal is paramount for battlefield safety. This study integrates high-throughput computational screening (HTCS) with advanced machine learning (ML) techniques to investigate the efficacy of metal-organic frameworks (MOFs) in adsorbing and capturing trace amounts of HD present in the air. Our approach commenced with a comprehensive univariate analysis, scrutinizing the impact of six distinct descriptors on the adsorption efficiency of MOFs. This analysis elucidated a pronounced correlation between MOF density and the Henry coefficient in the effective capture of HD. Then, four ML algorithms were employed to train and predict the performance of MOFs. The Random Forest (RF) algorithm demonstrates strong model learning and good generalization, achieving the best prediction result of 98.3%. In a novel exploratory stride, we incorporated a 166-bit MACCS molecular fingerprinting (MF) to identify critical functional groups within adsorbents. From the top 100 MOFs analyzed, 22 optimal functional groups were identified. Leveraging these insights, we designed three innovative substructures, grounded in these key functional groups, to enhance HD adsorption efficiency. In this work, the combination of MF and ML could provide a new direction for efficient screening of MOFs for the capture of HD in the air. The outcomes of this study offer substantial potential to revolutionize the domain of CWA capture. This represents a significant stride toward developing practical solutions that enhance both environmental protection and battlefield security.

Addressing Hospital Overwhelm During the COVID-19 Pandemic by Using a Primary Health Care-Based Integrated Health System: Modeling Study.

Background: After strict COVID-19-related restrictions were lifted, health systems globally were overwhelmed. Much has been discussed about how health systems could better prepare for future pandemics; however, primary health care (PHC) has been largely ignored. Objective: We aimed to investigate what combined policies PHC could apply to strengthen the health care system via a bottom-up approach, so as to better respond to a public health emergency. Methods: We developed a system dynamics model to replicate Shanghai's response when COVID-19-related restrictions were lifted. We then simulated an alternative PHC-based integrated health system and tested the following three interventions: first contact in PHC with telemedicine services, recommendation to secondary care, and return to PHC for recovery. Results: The simulation results showed that each selected intervention could alleviate hospital overwhelm. Increasing the rate of first contact in PHC with telemedicine increased hospital bed availability by 6% to 12% and reduced the cumulative number of deaths by 35%. More precise recommendations had a limited impact on hospital overwhelm (<1%), but the simulation results showed that underrecommendation (rate: 80%) would result in a 19% increase in cumulative deaths. Increasing the rate of return to PHC from 5% to 20% improved hospital bed availability by 6% to 16% and reduced the cumulative number of deaths by 46%. Moreover, combining all 3 interventions had a multiplier effect; bed availability increased by 683%, and the cumulative number of deaths dropped by 75%. Conclusions: Rather than focusing on the allocation of medical resources in secondary care, we determined that an optimal PHC-based integrated strategy would be to have a 60% rate of first contact in PHC, a 110% recommendation rate, and a 20% rate of return to PHC. This could increase health system resilience during public health emergencies.