Selective Elimination Research Articles

An improved modulation method for modular multilevel converters based on particle swarm optimization

Modular multilevel converter (MMC) is the first topology choice for flexible DC transmission systems. This paper presents a particle swarm optimization (PSO) algorithm aided modulation method to calculate the improved selective harmonic elimination pulse width modulation (iSHE-PWM) switching angles with the aim of reducing the total harmonic distortion (THD) and output voltage error of MMC. The SHE-PWM has more controllable variables compared with the staircase modulation so that it can be used to improve the output current waveform quality. This method retains the advantages of easy to control and low frequency from the staircase modulation. But amplitude of its high-order harmonic is high and this paper improves it. Firstly the mathematical model of MMC is set up and corresponding expressions of THD and voltage error are given. The joint function of THD and voltage error is considered as the fitness function. The PSO algorithm was used to minimize the joint function for solving the optimal switching angles. Finally the proposed method is verified through simulation results showing its potential to successfully solve the problem of difficulty in obtaining the iSHE-PWM switching angles while minimizing the THD and output voltage error of the MMC.

Tunable sulphur doping on CuFe2O4 nanostructures for the selective elimination of organic dyes from water

In this work, sulphur doped copper ferrites (S-CuFe2O4) photocatalysts were successfully synthesized for the first time using the facile hydrothermal method. The as-synthesized photocatalysts were characterized through XRD, Raman, TGA, FT-IR, UV–Vis-DRS, SEM, EDX and PL techniques. The results revealed that doping with sulphur has been found to be a suitable alternative that causes strain in the lattices as anions replace the oxygen from the CuFe2O4 nanostructures. Due to sulphur dopants, photocatalysts are able to efficiently trap and transfer the photoinduced charges, which readily suppress charge recombination. A UV–Vis spectrophotometer was used to monitor the degradation of selective toxic organic dyes (RhB, CR, MO, and CV) in aqueous media. The dye degradation results provide evidence for the surprisingly superior performance of S-CuFe2O4 over pristine CuFe2O4. On the basis of its efficiencies, this work can be assigned as an excellent candidate for photocatalysis science.

Support Vector Machine – Recursive Feature Elimination for Feature Selection on Multi-omics Lung Cancer Data

Biological data obtained from sequencing technologies is growing exponentially. Multi-omics data is one of the biological data that exhibits high dimensionality, or more commonly known as the curse of dimensionality. The curse of dimensionality occurs when the dataset contains many features or attributes but with significantly fewer samples or observations. The study focuses on mitigating the curse of dimensionality by implementing Support Vector Machine – Recursive Feature Elimination (SVM-RFE) as the selected feature selection method in the lung cancer (LUSC) multi-omics dataset integrated from three single omics dataset comprising genomics, transcriptomics and epigenomics, and assess the quality of the selected feature subsets using SDAE and VAE deep learning classifiers. In this study, the LUSC datasets first undergo data pre-processing, including checking for missing values, normalization, and removing zero variance features. The cleaned LUSC datasets are then integrated to form a multi-omics dataset. Feature selection was performed on the LUSC multi-omics data using SVM-RFE to select several optimal feature subsets. The five smallest feature subsets (FS) are used in classification using SDAE and VAE neural networks to assess the quality of the feature subsets. The results show that all 5 VAE models can obtain an accuracy and AUC score of 1.000, while only 2 out of 5 SDAE models (FS 1000 & 4000) can do so. 3 out of 5 SDAE models have an AUC score of 0.500, indicating zero capability in separating the binary class labels. The study concludes that a fine-tuned supervised learning VAE model has better capability in classification tasks compared to SDAE models for this specific study. Additionally, 1000 and 4000 are the two most optimal feature subsets selected by the SVM-RFE algorithm. The SDAE and VAE models built with these feature subsets achieve the best classification results.

Abstract 4969: Enhancing the efficacy of small molecule inhibitor of TRIP13 in prostate cancer using thymoquinone

Abstract Prostate cancer (PCa) is one of the leading causes of cancer-related death in men worldwide. Chemotherapy is effective in the early management of PCa; long-term use activates drug efflux pumps, resulting in resistance and recurrence. In this context, finding the genetic changes causing PCa development could significantly alter therapeutic results. The approach has been to search for specific molecular targets for the selective elimination of cancer cells. Small molecule inhibitor drugs have successfully targeted cancer cell growth and metastasis promotion. Still, small molecule inhibitors bind to multiple molecular targets, including cell surface receptors and other intracellular proteins, thus increasing the risk of toxicity and having a short life span. Therefore, it is crucial to identify new anti-cancer agents that work with small molecule inhibitors to target cancer cells while preventing normal cells. It has been reported that overexpression of the Thyroid hormone receptor interactor 13 (TRIP13) gene, a critical mitosis regulator, plays a role in many cancers. Our analysis using UALCAN (ualcan.path.uab.edu) showed overexpression of TRIP13 in PCa and it plays a role in PCa biology. When TRIP13 is overexpressed, it phosphorylates EGFR and activates a downstream pathway, making cancer cells more aggressive. Recently, DCZ0415, a small molecule TRIP13 inhibitor, was reported to prevent cell proliferation and invasion in several malignancies. Nevertheless, the therapeutic targeting of TRIP13 driving PCa is not well understood. In this study, we demonstrated Thymoquinone (TQ), a natural compound with multifaceted chemo-preventive potential and anti-cancer agent, could reinforce the effect of DCZ0415 in PCa cell lines (DU145 and PC3). PCa cells were treated with TQ or DCZ0415 alone or combined, followed by cell viability (MTT assay) to determine the optimal IC50 values. In a western blot, RT-qPCR analysis, and flow cytometry assays, the combined drug treatment was most effective in blocking TRIP13, inhibiting cell proliferation, and inducing apoptosis. Furthermore, this study determines the combination can upregulate the expression of cell cycle inhibitor (p21WAF1/CIP1), which, in turn, inhibits the expression of CDK4/Cyclin D1 complex, resulting the cell cycle arrest. In addition, TQ, in combination, downregulates the activation of EGFR-dependent PI3K/Akt-1/ERK1/2 and epithelial-mesenchymal transition (EMT) pathways in both cell lines. In conclusion, these findings show thymoquinone's potential to improve DCZ0415 effectiveness and suggest a new promising anti-cancer strategy for treating patients with prostate cancer. Citation Format: Santosh K. Singh, Manoj K. Mishra, Sooryanarayana Varambally, Rajesh Singh. Enhancing the efficacy of small molecule inhibitor of TRIP13 in prostate cancer using thymoquinone. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4969.

Abstract 85: Senescent cells promote breast cancer tumorigenesis

Abstract Age is the largest risk factor for breast cancer development. While numerous changes arise with age, we posit that the accumulation of p16INKA4 (p16)+ senescent stromal cells—which express cytokines, chemokines, and enzymes together recognized as senescence-associated secretory phenotype (SASP)—promote cancer progression. Indeed, high p16 positivity in stroma strongly correlates with breast cancer recurrence. To investigate how senescent stroma impact tumorigenesis, we crossed MMTV-PyMT (PyMT) mice that spontaneously develop mammary tumors to INK-ATTAC (INK) mice, which allows selective elimination of p16+ cells. Depletion of p16+ stroma in PyMT/INK mice led to a significantly delayed tumor onset and changes in tumor-infiltrating immune cells, both of which could be recapitulated by treating PyMT mice with a senolytic drug. scRNA-seq analyses of murine and human tumor samples revealed that senescence is restricted to a specific cancer associated fibroblasts (CAF) subpopulation that expresses numerous immune and extracellular matrix SASP factors that could impact T cells and Natural Killer (NK) cells. We refer to these cells as senescent CAFs (senCAFs). To assess the impact of senCAFs on T and NK cells’ anti-tumor effect, we depleted each population and found that the elimination of senCAFs no longer restricted tumor development in the absence of NK cells. We thus focused on addressing how senCAFs modulate NK cell function. Together our data highlight how senescent CAFs contribute to mammary gland tumorigenesis by modifying tumor microenvironment. Citation Format: Jiayu (Jennifer) Ye, Ana Paula Delgado, Qihao Ren, Robert S. Powers, Sheila A. Stewart. Senescent cells promote breast cancer tumorigenesis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 85.

MLL3/MLL4 methyltransferase activities control early embryonic development and embryonic stem cell differentiation in a lineage-selective manner.

H3K4me1 methyltransferases MLL3 (KMT2C) and MLL4 (KMT2D) are critical for enhancer activation, cell differentiation and development. However, roles of MLL3/4 enzymatic activities and MLL3/4-mediated enhancer H3K4me1 in these processes remain unclear. Here we report that constitutive elimination of both MLL3 and MLL4 enzymatic activities prevents initiation of gastrulation and leads to early embryonic lethality in mice. However, selective elimination of MLL3/4 enzymatic activities in embryonic, but not extraembryonic, lineages leaves gastrulation largely intact. Consistent with this, embryonic stem cells (ESCs) lacking MLL3/4 enzymatic activities can differentiate toward the three embryonic germ layers but show aberrant differentiation to extraembryonic endoderm (ExEn) and trophectoderm. The failure in ExEn differentiation can be attributed to markedly reduced enhancer-binding of the lineage-determining transcription factor GATA6. Furthermore, we show that MLL3/4-catalyzed H3K4me1 is largely dispensable for enhancer activation during ESC differentiation. Together, our findings suggest a lineage-selective, but enhancer activation-independent, role of MLL3/4 methyltransferase activities in early embryonic development and ESC differentiation.

PD-L1ATTAC mice reveal the potential of depleting PD-L1 expressing cells in cancer therapy

Antibodies targeting the PD-1 receptor and its ligand PD-L1 have shown impressive responses in some tumors of bad prognosis. We hypothesized that, since immunosuppressive cells might present several immune checkpoints on their surface, the selective elimination of PD-L1 expressing cells could be efficacious in enabling the activation of antitumoral immune responses. To address this question, we developed an inducible suicidal knock-in mouse allele of Pd-l1 (PD-L1ATTAC) which allows for the tracking and specific elimination of PD-L1-expressing cells in adult tissues. Consistent with our hypothesis, elimination of PD-L1 expressing cells from the mouse peritoneum increased the septic response to lipopolysaccharide (LPS), due to an exacerbated inflammatory response to the endotoxin. In addition, mice depleted of PD-L1+ cells were resistant to colon cancer peritoneal allografts, which was associated with a loss of immunosuppressive B cells and macrophages, concomitant with an increase in activated cytotoxic CD8 T cells. Collectively, these results illustrate the usefulness of PD-L1ATTAC mice for research in immunotherapy and provide genetic support to the concept of targeting PD-L1 expressing cells in cancer.

Hybrid low switching frequency modulation strategy with high dynamic response for high‐power voltage source converter

AbstractFor high‐power converters, the low switching frequency (SF) modulation represented by selective harmonic elimination pulse width modulation (SHE‐PWM) is crucial to reduce the switching loss and enhance the efficiency with a good steady‐state performance. However, since the advantages of SHE‐PWM mainly come from the fixed switching angle distribution limited by non‐linear equations, switching angles should be adjusted slowly. This requires that the bandwidth of proportional integral (PI) controllers be limited hugely, resulting in a poor dynamic response. As the most popular control to improve the dynamic response, finite‐control‐set model predictive control (FCS‐MPC) has a worse steady‐state performance under low SF because of large errors caused by a long prediction period and harmonics caused by space vector PWM (SVPWM). Therefore, a hybrid modulation strategy with an acceptable complexity is proposed in this article, which combines SHE‐PWM and FCS‐MPC. PI + SHE‐PWM is adopted in a steady state with low SF, while MPC + SVPWM is used in a transient state with high SF. By studying smooth switching from the modulation level and control level, the proposed method can eliminate the current surge when switching between PI + SHE‐PWM and MPC + SVPWM. Experiments verify that the proposed method have a good steady‐state performance and high dynamic response simultaneously under overall low SF.

Release from sexual selection leads to rapid genome-wide evolution in Aedes aegypti

The yellow fever mosquito, Aedes aegypti, mates in flight as part of ephemeral aggregations termed swarms. Swarms contain many more males than females, and males are thought to be subject to intense sexual selection.1,2 However, which male traits are involved in mating success and the genetic basis of these traits remains unclear. We used an experimental evolution approach to measure genome-wide responses of Ae. aegypti evolved in the presence and absence of sexual selection. These data revealed for the first time how sexual selection shapes the genome of this important species. We found that populations evolved under sexual selection retained greater genetic similarity to the ancestral population and a higher effective population size than populations evolving without sexual selection. When we compared evolutionary regimes, we found that genes associated with chemosensation responded rapidly to the elimination of sexual selection. Knockdown of one high-confidence candidate gene identified in our analysis significantly decreased male insemination success, further suggesting that genes related to male sensory perception are under sexual selection. Several mosquito control technologies involve the release of males from captive populations into the wild. For these interventions to work, a released male must compete against wild males to successfully inseminate a female. Our results suggest that maintaining the intensity of sexual selection in captive populations used in mass-releases is important for sustaining both male competitive ability and overall genetic similarity to field populations.

Machine Learning Identification of Obstructive Sleep Apnea Severity through the Patient Clinical Features: A Retrospective Study.

To evaluate the role of clinical scores assessing the risk of disease severity in patients with clinical suspicion of obstructive sleep apnea syndrome (OSA). The hypothesis was tested by applying artificial intelligence (AI) to demonstrate its effectiveness in distinguishing between mild-moderate OSA and severe OSA risk. A support vector machine model (SVM) was developed from the samples included in the analysis (N = 498), and they were split into 75% for training (N = 373) with the remaining for testing (N = 125). Two diagnostic thresholds were selected for OSA severity: mild to moderate (apnea-hypopnea index (AHI) ≥ 5 events/h and AHI < 30 events/h) and severe (AHI ≥ 30 events/h). The algorithms were trained and tested to predict OSA patient severity. The sensitivity and specificity for the SVM model were 0.93 and 0.80 with an accuracy of 0.86; instead, the logistic regression full mode reported a value of 0.74 and 0.63, respectively, with an accuracy of 0.68. After backward stepwise elimination for features selection, the reduced logistic regression model demonstrated a sensitivity and specificity of 0.79 and 0.56, respectively, and an accuracy of 0.67. Artificial intelligence could be applied to patients with symptoms related to OSA to identify individuals with a severe OSA risk with clinical-based algorithms in the OSA framework.

Total Synthesis of Lineaflavones A, C, D, and Analogues

The first total synthesis of lineaflavones A, C, D, and their analogues has been accomplished. The key synthetic steps include aldol/oxa-Michael/dehydration sequence reactions to assemble the tricyclic core, Claisen rearrangement and Schenck ene reaction to construct the key intermediate, and selective substitution or elimination of tertiary allylic alcohol to obtain natural compounds. In addition, we also explored five new routes to synthesize fifty-three natural product analogues, which can contribute to a systematic structure-activity relationship during biological evaluation.

SHEPWM in three-phase voltage source inverters by modified Newton–Raphson

&lt;span lang="EN-US"&gt;This paper describes a new strategy for optimizing the switching angles of a three-phase inverter in a photovoltaic system. It presents non-traditional solutions to the problem of selective harmonic elimination (SHE) in three-phase inverter (VSI)-fed induction motor drives. The aforementioned problem was solved independently by using hybrid genetic algorithms (HGAs) and a modified Newton–Raphson method. GAs can obtain the correct solution even if the first generation is arbitrary. The solution then converges rapidly. The modified Newton–Raphson method is used to solve transcendental equations of the SHE pulses width modulation (SHEPWM) technique, which is a unique method that produces all possible solutions without assuming the initial angles. This modified technique is not complex and ensures rapid convergence to the solution. A real-time experimental verification of the SHEPWM technique was performed in the OP5600 RT-Lab simulator. The results obtained show that the proposed SHEPWM algorithm controls the fundamental voltage and effectively eliminates the desired harmonics, and that the evolution of the signal quality increases according to the modulation index. For M=1.1 the SHE-PWM gives the best result: a current THD of 5% for a switching frequency of 1150 Hz.&lt;/span&gt;

Effects of molecular structure and existing forms on degradation of emerging contaminants by LaFeO3/NDA−99−oxygen vacancy−driven photo−Fenton system

The selective elimination of emerging contaminants (ECs) by means of advanced oxidation processes is gaining more and more interest. The LaFeO3/NDA−99−oxygen vacancy−driven photo−Fenton system was chosen as a typical advanced oxidation process to investigate the effect of the previously neglected ECs molecular structure and existing forms on the degradation efficiency. Tetracycline antibiotics (TCs), quinolone antibiotics (QNs) and sulfonamide antibiotics (SAs) were used as target contaminants. TCs were found to have removal efficiencies more than 85.00% (91.52%, 88.68%, 86.55%, and 85.83%). Three parameters ((energy gap (ΔE, 27.50%), energy of the highest occupied molecular orbital (EHOMO, 17.00%), vertical ionization potential (VIP, 17.00%)) obtained the highest contributions (61.50% in total) on the removal efficiency. The effect of the existing forms on the removal efficiency in different pH was also explored. ECs in neutral form are more easily degraded. DFT calculation may anticipate the degradation pathways of different−structured contaminants based on intermediate detection and analysis. With the new insights gained from this research, wastewater treatment will have a theoretical foundation for optimizing the degradation potential of contaminants with varying molecular structures and existing forms.

Investigation of Recent Metaheuristics Based Selective Harmonic Elimination Problem for Different Levels of Multilevel Inverters

Multilevel inverters (MLI) are popular in high-power applications. MLIs are generally configured to have switches reduced by switching techniques that eliminate low-order harmonics. The selective harmonic elimination (SHE) method, which significantly reduces the number of switching, determines the optimal switching moments to obtain the desired output voltage and eliminates the desired harmonic components. To solve the SHE problem, classical methods are primarily employed. The disadvantages of such methods are the high probability of trapping in locally optimal solutions and their dependence on initial controlling parameters. One solution to overcome this problem is the use of metaheuristic algorithms. In this study, firstly, 22 metaheuristic algorithms with different sources of inspiration were used to solve the SHE problem at different levels of MLIs, and their performances were extensively analyzed. To reveal the method that offers the best solution, these algorithms were first applied to an 11-level MLI circuit, and six methods were determined as a result of the performance analysis. As a result of the evaluation, the outstanding methods were SPBO, BMO, GA, GWO, MFO, and SPSA. As a result of the application of superior methods to 7-, 11-, 15-, and 19-level MLIs according to the IEEE 519—2014 standard, it has been shown that BMO outperforms in 7-level MLI, GA in 11-level MLI, and SPBO in 15- and 19-level MLIs in terms of THD, while in terms of output voltage quality, GA in 7-level MLI, BMO in 11-level MLI, GA and SPSA in 15-level MLI, and SPSA in 19-level MLI come forward.

A strategy for improving the SHEPWM commutation speed of CSI through hybrid switches

High-power current source inverters (CSI) usually operate at a low switching frequency to reduce switching loss. To suppress low-order harmonics and simplify filter design, the selective harmonic elimination pulse width modulation (SHEPWM) technique is a feasible common modulation strategy in industrial applications. This paper proposes an operational strategy that uses an H7 current source inverter (H7-CSI) with hybrid switches to perform the SHEPWM technique. On the basis of retaining the conventional H6 inverter bridge, the commutation speed of the CSI is improved by an additional shunt-connected high-performance power switch. The proposed scheme solves the problem that the CSIs built with low-speed switches (such as GTOs) may have difficulty for implementing the setting pulse widths of null states, while further reducing the switching losses at an acceptable cost. In addition, mitigating the influence of overlap-time by optimizing the driving signal of the H6 converter bridge. Finally, simulation and experiments have verified the effectiveness of the proposed CSI scheme.

Investigation and validation of PV fed reduced switch asymmetric multilevel inverter using optimization based selective harmonic elimination technique

Pulse width modulation for Selective Harmonics Elimination (SHE) is mostly employed in the reduction of lower order harmonics. The PV system in this research provides input voltage to the reduced switch 31-level inverter, which is based on the Artificial Bee Colony algorithm. With a high gain DC-DC single-ended primary-inductor converter (SEPIC), the PV panel output voltage is kept constant. The Grey wolf optimization algorithm (GWO) approach is used to get the most power out PV scheme. Multi Carrier modulation, a high-frequency modulation technology, is also used in this novel design of the inverter to reduce upper order harmonics. The suggested Artificial Bee Colony (ABC) algorithm, harmonics is compared to a SHE technique based on a genetic algorithm. The hardware findings were confirmed using DSPIC30F2010 controller simulation, and the recommended system was validated using Matlab simulation.

Genetic models of cleavage-reduced and soluble TREM2 reveal distinct effects on myelination and microglia function in the cuprizone model

Triggering receptor expressed on myeloid cells 2 (TREM2) is a cell-surface immunoreceptor expressed on microglia, osteoclasts, dendritic cells and macrophages. Heterozygous loss-of-function mutations in TREM2, including mutations enhancing shedding form the cell surface, have been associated with myelin/neuronal loss and neuroinflammation in neurodegenerative diseases, such as Alzheimer`s disease and Frontotemporal Dementia. Using the cuprizone model, we investigated the involvement of soluble and cleavage-reduced TREM2 on central myelination processes in cleavage-reduced (TREM2-IPD), soluble-only (TREM2-sol), knockout (TREM2-KO) and wild-type (WT) mice. The TREM2-sol mouse is a new model with selective elimination of plasma membrane TREM2 and a reduced expression of soluble TREM2. In the acute cuprizone model demyelination and remyelination events were reflected by a T2-weighted signal intensity change in magnetic resonance imaging (MRI), most prominently in the external capsule (EC). In contrast to WT and TREM2-IPD, TREM2-sol and TREM2-KO showed an additional increase in MRI signal during the recovery phase. Histological analyses of TREM2-IPD animals revealed no recovery of neuroinflammation as well as of the lysosomal marker LAMP-1 and displayed enhanced cytokine/chemokine levels in the brain. TREM2-sol and, to a much lesser extent, TREM2-KO, however, despite presenting reduced levels of some cytokines/chemokines, showed persistent microgliosis and astrocytosis during recovery, with both homeostatic (TMEM119) as well as activated (LAMP-1) microglia markers increased. This was accompanied, specifically in the EC, by no myelin recovery, with appearance of myelin debris and axonal pathology, while oligodendrocytes recovered. In the chronic model consisting of 12-week cuprizone administration followed by 3-week recovery TREM2-IPD displayed sustained microgliosis and enhanced remyelination in the recovery phase. Taken together, our data suggest that sustained microglia activation led to increased remyelination, whereas microglia without plasma membrane TREM2 and only soluble TREM2 had reduced phagocytic activity despite efficient lysosomal function, as observed in bone marrow-derived macrophages, leading to a dysfunctional phenotype with improper myelin debris removal, lack of remyelination and axonal pathology following cuprizone intoxication.

Mitigation Technique for Cascaded H-Bridge Multilevel Inverters Based on Pulse Active Width Modulation

This article considers <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${l}$ </tex-math></inline-formula> -level cascaded H-bridge (CHB) inverters and proposes a new modulation method based on pulse active width modulation (PAWM), capable to minimize all harmonics with order <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$n&lt; 2l+1$ </tex-math></inline-formula> and to satisfy the European harmonic standards for medium-voltage-level applications EN 50 160 and CIGRE WG 36-05. A mathematical theorem and its proof are presented, stating the features of the procedure, which is an improvement of the selective harmonic elimination (SHE) PAWM proposed by Buccella et al. After a detailed description of the method, simulation and experimental results have been included, showing its capability to reduce low-order harmonics.

Specific nanoantibiotics for selective removal of antibiotic-resistant bacteria: New insights in bacterial imprinting based on interfacial biomimetic mineralization

Antibiotic resistance has been a worsening global concern and selective elimination of antibiotic-resistant bacteria (ARB) while retaining the co-existed beneficial bacteria has been essential in environmental protection, which having attracted considerable interest. In this work, by integrating the whole cell imprinting and epitope imprinting strategy, magnetic bacterial imprinted polymers (BIPs) towards ARB were synthesized with interfacial biomimetic mineralization followed by a screening process. The binding data showed that the BIPs owned highly specific affinity towards the target bacteria. Taking advantage of this specific binding ability of BIPs, a two-step selective antimicrobial approach was developed. Remarkably, the BIP nanoantibiotics (nAbts) could efficiently destroy ARB without harming the beneficial bacteria. In comparison with the non-bacterial imprinted polymers, the biocompatible BIP nAbts showed a 12.5-fold increase in the survival percentage for the beneficial bacteria in wastewater. To the best of our knowledge, this is the first time that bacterial imprinting via interfacial biomimetic mineralization was developed, and also the first report of killing ARB without harming the beneficial bacteria in wastewater. We believe that this strategy provides a new insight into the design of novel affinity materials for the selective elimination of ARB in biological treatment for environmental protection.

Superhydrophobic fluorinated nanoparticle-modified surfaces for fast, efficient, and selective elimination of oil from water

An effective, low-cost method for fabricating superhydrophobic surfaces was investigated. A mixed solution of tetrahydrofuran, 2,3,4,5,6-pentafluorostyrene, and Al₂O₃ nanoparticles was introduced to the original materials to obtain superhydrophobic modified polypropylene (M-PP), cotton fiber (M-CTF), and polyurethane foam (M-PUF). The novelty of this work includes the development of cost-effective, stable materials with superhydrophobic surfaces for extreme water-repellency. The prepared materials were evaluated for hydrophobicity, oil absorption capacity, separation efficiency, oil flux, and reusability using several techniques. They all showed superhydrophobicity with water contact angles higher than 151 ± 0.5°. The results also reveal that the materials exhibited significant oil absorption capacities between 9.8 and 40.3 times their own weights, high separation efficiency (>97.2%), oil flux (>41,110 Lm⁻²h⁻¹), and reusability (>100 times) in the separation of oil-water. Moreover, all the treated materials demonstrated excellent oil selectivity in different salty waters. The samples could still retain outstanding separation even after 10 abrasion cycles with sandpapers. The excellent anti-intrusion and anti-abrasion behavior make the prepared materials promising for oil/water separation in harsh environments.