Effect of Nitrogen Doping on the Photocatalytic Properties and Antibiofilm Efficacy of Reduced TiO2 Nanoparticles.

Nanomaterial-mediated antibacterial photodynamic therapy (aPDT) emerges as a promising treatment against antibiotic-resistant bacterial biofilms. Specifically, titanium dioxide nanoparticles (TiO2 NPs) are being investigated as photosensitizers in aPDT to address biofilm related diseases. To enhance their photocatalytic performance in the visible spectral range for biomedical applications, various strategies have been adopted, including reduction of TiO2 NPs. However, despite improvements in visible-light photoactivity, reduced TiO2 NPs have yet to reach their expected performance primarily due to the instability of oxygen vacancies and their tendency to reoxidize easily. To address this, we present a two-step approach to fabricate highly visible-light active and stable TiO2 NP photocatalysts, involving nitrogen doping followed by a magnesium-assisted reductive annealing process. X-ray photoelectron spectroscopy analysis of the synthesized reduced nitrogen-doped TiO2 NPs (H:Mg-N-TiO2 NPs) reveals that the presence of nitrogen stabilizes oxygen vacancies and reduced Ti species, leading to increased production of reactive oxygen species under visible-light excitation. The improved aPDT efficiency translates to a 3-fold enhancement in the antibiofilm activity of nitrogen-doped compared to undoped reduced TiO2 NPs against both Gram-positive (Streptococcus mutans) and Gram-negative (Porphyromonas gingivalis, Fusobacterium nucleatum) oral pathogens. These results underscore the potential of H:Mg-N-TiO2 NPs in aPDT for combating bacterial biofilms effectively.

Early Arthrocentesis for Temporomandibular Joint Arthralgia: A Superiority Trial.

OBJECTIVES: The aim of this superiority trial was to investigate the clinical outcomes of arthrocentesis as an early treatment supported by use of an occlusal splint vs use of an occlusal splint only in the management of temporomandibular joint (TMJ) arthralgia. METHODS: Ninety-five adults presenting with TMJ arthralgia were recruited into the study and randomised into 2 groups: Group 1 received arthrocentesis as an early treatment supported by use of an occlusal splint, whereas group 2 received treatment with an occlusal splint only. Seventy-four patients (group 1: n = 37; group 2: n = 37) completed the 1-year follow-up schedule and were included in the final analysis. Reduction of pain intensity measured by a numeric rating scale and increase in mouth opening distance (unassisted maximal, assisted maximal, and pain-free) was seen in both treatment groups. RESULTS: In group 1, pain intensity significantly decreased at 6 weeks and all subsequent time points compared with group 2. In terms of mouth opening distance, a significant improvement was observed in both groups during the course of treatment, but statistical significance was not seen between the 2 treatment groups. CONCLUSIONS: Early arthrocentesis supported by use of an occlusal splint is superior to use of an occlusal splint alone in the treatment of TMJ arthralgia. Arthrocentesis with occlusal splint support could be discussed as first-line treatment for arthralgia of the TMJ, which may co-occur with various painful and nonpainful conditions of TMJ disorders.

A novel interpretable machine learning model approach for the prediction of TiO2 photocatalytic degradation of air contaminants.

Air contaminants lead to various environmental and health issues. Titanium dioxide (TiO2) features the benefits of autogenous photocatalytic degradation of air contaminants. To evaluate its performance, laboratory experiments are commonly used to determine the kinetics of the photocatalytic-degradation rate, which is labor intensive, time-consuming, and costly. In this study, Machine Learning (ML) models were developed to predict the photo-degradation rate constants of air-borne organic contaminants with TiO2 nanoparticles and ultraviolet irradiation. The hyperparameters of the ML models were optimized, which included Artificial Neural Network (ANN) with Bayesian optimization, gradient booster regressor (GBR) with Bayesian optimization, Extreme Gradient Boosting (XGBoost) with optimization using Hyperopt, and Catboost combined with Adaboost. The organic contaminant was encoded through Molecular fingerprints (MF). Imputation method was applied to deal with the missing data. A generative ML model Vanilla Gan was utilized to create synthetic data to further augment the size of available dataset and the SHapley Additive exPlanations (SHAP) was employed for ML model interpretability. The results indicated that data imputation allowed for the full utilization of the limited dataset, leading to good machine learning prediction performance and preventing common overfitting problems with small-sized data. Additionally, augmenting experimental data with synthetic data significantly improved prediction accuracy and considerably reduced overfitting issues. The results ranked the feature importance and assessed the impacts of different experimental variables on the rate of photo-degradation, which were consistent with physico-chemical laws.

A validated LC-MS/MS method for the quantitation of daratumumab in rat serum using rapid tryptic digestion without IgG purification and reduction.

Daratumumab, a humanized monoclonal antibody utilized in treating immunoglobulin light-chain amyloidosis and relapsed/refractory multiple myeloma, was quantified in rat serum through a simple, economical and effective liquid chromatography tandem-mass spectrometry (LC-MS/MS) method. A surrogate peptide, LLIYDASNR, derived from trypsin hydrolysis, was quantitatively analyzed with LLIYDASN [13C6, 15N4] RAT as an internal standard. This corrected variations from sample pretreatment and mass spectrometry response, involving denaturation and trypsin hydrolysis in a two-step process lasting approximately 1 hour. Methodological validation demonstrated a linear range of 1 µg/mL to 1000 µg/mL in rat serum. Precision, accuracy, matrix effect, sensitivity, stability, selectivity, carryover, and interference met acceptance criteria. The validated LC-MS/MS approach was successfully applied to a pharmacokinetic study of daratumumab in rats at an intravenous dose of 15 mg/kg.

Long-term stability of jaw reconstruction with microvascular bone flaps: A prospective longitudinal study.

OBJECTIVES: Microvascular bone flap jaw reconstruction has achieved satisfactory clinical outcomes. However, little is known about the long-term stability of the reconstructed jaw. This prospective longitudinal study aimed to investigate the long-term stability of jaw reconstruction and factors that were associated with it. METHODS: Patients with successful computer-assisted osseous free-flap jaw reconstruction in the Department of Oral and Maxillofacial Surgery, Queen Mary Hospital, Hong Kong were recruited for this prospective longitudinal study. The three-dimensional jaw models at the pre-operative plan, post-operative 1-month, and 2 years were aligned and compared. RESULTS: A total of 69 patients were recruited, among which 48 patients were available for the long-term analysis. Compared to 1-month after surgery, further deviation from the pre-operative plan was observed at post-operative 2 years. Lack of accuracy in surgery, segmental mandible resection especially with the involvement of mandible angles, and post-operative radiation therapy were identified as the significant factors affecting the positional stability of the reconstructed jaw (p < 0.05). Stable reconstruction was observed in the subgroup analysis of patients without post-operative radiation therapy. CONCLUSION: Up to the best of our knowledge, this is the first prospective longitudinal study reporting the long-term stability of jaw reconstruction and its affecting factors. Our data demonstrated that the reconstructed jaw position lacked stability over the postoperative period. How to improve long-term stability of reconstructed jaw thus optimize the functional outcomes warrants further studies.

Targeting and monitoring ovarian cancer invasion with an RNAi and peptide delivery system.

RNA interference (RNAi) therapeutics are an emerging class of medicines that selectively target mRNA transcripts to silence protein production and combat disease. Despite the recent progress, a generalizable approach for monitoring the efficacy of RNAi therapeutics without invasive biopsy remains a challenge. Here, we describe the development of a self-reporting, theranostic nanoparticle that delivers siRNA to silence a protein that drives cancer progression while also monitoring the functional activity of its downstream targets. Our therapeutic target is the transcription factor SMARCE1, which was previously identified as a key driver of invasion in early-stage breast cancer. Using a doxycycline-inducible shRNA knockdown in OVCAR8 ovarian cancer cells both in vitro and in vivo, we demonstrate that SMARCE1 is a master regulator of genes encoding proinvasive proteases in a model of human ovarian cancer. We additionally map the peptide cleavage profiles of SMARCE1-regulated proteases so as to design a readout for downstream enzymatic activity. To demonstrate the therapeutic and diagnostic potential of our approach, we engineered self-assembled layer-by-layer nanoparticles that can encapsulate nucleic acid cargo and be decorated with peptide substrates that release a urinary reporter upon exposure to SMARCE1-related proteases. In an orthotopic ovarian cancer xenograft model, theranostic nanoparticles were able to knockdown SMARCE1 which was in turn reported through a reduction in protease-activated urinary reporters. These LBL nanoparticles both silence gene products by delivering siRNA and noninvasively report on downstream target activity by delivering synthetic biomarkers to sites of disease, enabling dose-finding studies as well as longitudinal assessments of efficacy.

Radiographic Imaging for the Diagnosis and Treatment of Patients with Skeletal Class III Malocclusion.

Skeletal Class III malocclusion is one type of dentofacial deformity that significantly affects patients' facial aesthetics and oral health. The orthodontic treatment of skeletal Class III malocclusion presents challenges due to uncertainties surrounding mandibular growth patterns and treatment outcomes. In recent years, disease-specific radiographic features have garnered interest from researchers in various fields including orthodontics, for their exceptional performance in enhancing diagnostic precision and treatment effect predictability. The aim of this narrative review is to provide an overview of the valuable radiographic features in the diagnosis and management of skeletal Class III malocclusion. Based on the existing literature, a series of analyses on lateral cephalograms have been concluded to identify the significant variables related to facial type classification, growth prediction, and decision-making for tooth extractions and orthognathic surgery in patients with skeletal Class III malocclusion. Furthermore, we summarize the parameters regarding the inter-maxillary relationship, as well as different anatomical structures including the maxilla, mandible, craniofacial base, and soft tissues from conventional and machine learning statistical models. Several distinct radiographic features for Class III malocclusion have also been preliminarily observed using cone beam computed tomography (CBCT) and magnetic resonance imaging (MRI).

Nano-PROTACs: state of the art and perspectives.

PROteolysis TArgeting Chimeras (PROTACs), as a recently identified technique in the field of new drug development, provide new concepts for disease treatment and are expected to revolutionize drug discovery. With high specificity and flexibility, PROTACs serve as an innovative research tool to target and degrade disease-relevant proteins that are not currently pharmaceutically vulnerable to eliminating their functions by hijacking the ubiquitin-proteasome system. To date, PROTACs still face the challenges of low solubility, poor permeability, off-target effects, and metabolic instability. The combination of nanotechnology and PROTACs has been explored to enhance the in vivo performance of PROTACs regarding overcoming these challenging hurdles. In this review, we summarize the latest advancements in the building-block design of PROTAC prodrug nanoparticles and provide an overview of existing/potential delivery systems and loading approaches for PROTAC drugs. Furthermore, we discuss the current status and prospects of the split-and-mix approach for PROTAC drug optimization. Additionally, the advantages and translational potentials of carrier-free nano-PROTACs and their combinational therapeutic effects are highlighted. This review aims to foster a deeper understanding of this rapidly evolving field and facilitate the progress of nano-PROTACs that will continue to push the boundaries of achieving selectivity and controlled release of PROTAC drugs.

Lingual Denervation Improves the Efficacy of Anti-PD-1 Immunotherapy in Oral Squamous Cell Carcinomas by Downregulating TGFß Signaling.

PURPOSE: Intratumoral nerve infiltration relates to tumor progression and poor survival in oral squamous cell carcinoma (OSCC). How neural involvement regulates antitumor immunity has not been well characterized. This study aims to investigate molecular mechanisms of regulating tumor aggressiveness and impairing antitumor immunity by nerve-derived factors. EXPERIMENTAL DESIGN: We performed the surgical lingual denervation in an immunocompetent mouse OSCC model to investigate its effect on tumor growth and the efficacy of anti-PD-1 immunotherapy. A trigeminal ganglion neuron and OSCC cell coculture system was established to investigate the proliferation, migration, and invasion of tumor cells and the PD-L1 expression. Both the neuron-tumor cell coculture in vitro model and the OSCC animal model were explored. RESULTS: Lingual denervation slowed down tumor growth and improved the efficacy of anti-PD-1 treatment in the OSCC model. Coculturing with neurons not only enhanced the proliferation, migration, and invasion but also upregulated TGFß-SMAD2 signaling and PD-L1 expression of tumor cells. Treatment with the TGFß signaling inhibitor galunisertib reversed nerve-derived tumor aggressiveness and downregulated PD-L1 on tumor cells. Similarly, lingual denervation in vivo decreased TGFß and PD-L1 expression and increased CD8+ T-cell infiltration and the expression of IFNγ and TNFα within tumor. CONCLUSIONS: Neural involvement enhanced tumor aggressiveness through upregulating TGFß signaling and PD-L1 expression in OSCC, while denervation of OSCC inhibited tumor growth, downregulated TGFß signaling, enhanced activities of CD8+ T cells, and improved the efficacy of anti-PD-1 immunotherapy. This study will encourage further research focusing on denervation as a potential adjuvant therapeutic approach in OSCC. SIGNIFICANCE: This study revealed the specific mechanisms for nerve-derived cancer progression and impaired antitumor immunity in OSCC, providing a novel insight into the cancer-neuron-immune network as well as pointing the way for new strategies targeting nerve-cancer cross-talk as a potential adjuvant therapeutic approach for OSCC.

A robust and validated LC-MS/MS method for the quantification of ramucirumab in rat and human serum using direct enzymatic digestion without immunoassay.

A new liquid chromatography tandem mass spectrometry (LC-MS/MS) method was established to quantify the anti-gastric cancer fully human monoclonal antibody (ramucirumab) in rat and human serum. The surrogate peptide (GPSVLPLAPSSK) for ramucirumab was generated by trypsin hydrolysis and quantified using the isotopically labeled peptide GPSVLPLAPSSK[13C6, 15N2]ST containing two more amino acids at the carboxyl end as an internal standard to correct for variations introduced during the enzymatic hydrolysis process and any mass spectrometry changes. Additionally, the oxidation and deamidation of unstable peptides (VVSVLTVLHQDWLNGK and NSLYLQMNSLR) were detected. The quantitative range of the proposed method was 1-1000 µg/mL, and complete methodological validation was performed. The precision, accuracy, matrix effect, sensitivity, stability, selectivity, carryover, and interference of the measurements met the required standards. The validated LC-MS/MS method was applied to pharmacokinetic studies in rats administered ramucirumab at 15 mg/kg intravenously. Overall, a robust, efficient, and cost-effective LC-MS/MS method was successfully developed for quantifying ramucirumab in rat and human serum.

Leveraging artificial intelligence for perioperative cancer risk assessment of oral potentially malignant disorders.

Oral potentially malignant disorders (OPMDs) are mucosal conditions with an inherent disposition to develop oral squamous cell carcinoma. Surgical management is the most preferred strategy to prevent malignant transformation in OPMDs, and surgical approaches to treatment include conventional scalpel excision, laser surgery, cryotherapy, and photodynamic therapy. However, in reality, since all patients with OPMDs will not develop oral squamous cell carcinoma in their lifetime, there is a need to stratify patients according to their risk of malignant transformation to streamline surgical intervention for patients with the highest risks. Artificial intelligence (AI) has the potential to integrate disparate factors influencing malignant transformation for robust, precise, and personalized cancer risk stratification of OPMD patients than current methods to determine the need for surgical resection, excision, or re-excision. Therefore, this article overviews existing AI models and tools, presents a clinical implementation pathway, and discusses necessary refinements to aid the clinical application of AI-based platforms for cancer risk stratification of OPMDs in surgical practice.

A quantitative comparison of bone resection margin distances in virtual surgical planning versus histopathology: a prospective study.

BACKGROUND: Positive bone margins have been shown to be associated with worse locoregional control and survival performance in oral oncology patients. With the application of computer-assisted surgery and patient-specific surgical guides, the authors can accurately execute the preoperative osteotomy plan. However, how well the authors can predict the margin distance in the final histopathology with a preoperative computed tomography (CT) scan, the factors associated with it, and how much leeway CT should spare when designing the osteotomy planes during virtual surgical planning (VSP) remain to be investigated. MATERIALS AND METHODS: Patients from January 2021 to December 2022 with benign or malignant jaw tumors and with signs of bone marrow involvement in the preoperative CT scan in our center were prospectively recruited to the study. VSP and measurement of the closest margin distance in the CT scan were performed by the single team of surgeons. The resection specimen was processed, and the margin distances were measured by a dedicated senior pathologist with the knowledge of orientation of the osteotomy planes. RESULTS: A total of 35 patients were recruited, with 21 malignant and 14 benign cases. Sixty-eight bone margins were quantitatively analyzed. No significant difference in margin distances measured from the CT scan and final histopathology was detected ( P =0.19), and there was a strong correlation between the two (r s =0.74, P <0.01). A considerable amount of variance was detected in the level of discrepancy between margin distances measured in the CT scan and final histopathology (overall SD=6.26 mm, malignancy SD=7.44 mm, benign SD=4.40 mm). No significant correlation existed between the two margin distances when only maxilla tumor margins were assessed ( P =0.16). CONCLUSION: The bone margin distance in VSP is reliably correlated to the final pathological margin distance. A leeway distance of 15mm and 9mm should be considered when designing the osteotomy planes for malignancy and benign cases, respectively. Extra attention should be paid to maxilla cases when predetermining the osteotomy planes during VSP.

Artificial intelligence in salivary biomarker discovery and validation for oral diseases.

Salivary biomarkers can improve the efficacy, efficiency, and timeliness of oral and maxillofacial disease diagnosis and monitoring. Oral and maxillofacial conditions in which salivary biomarkers have been utilized for disease-related outcomes include periodontal diseases, dental caries, oral cancer, temporomandibular joint dysfunction, and salivary gland diseases. However, given the equivocal accuracy of salivary biomarkers during validation, incorporating contemporary analytical techniques for biomarker selection and operationalization from the abundant multi-omics data available may help improve biomarker performance. Artificial intelligence represents one such advanced approach that may optimize the potential of salivary biomarkers to diagnose and manage oral and maxillofacial diseases. Therefore, this review summarized the role and current application of techniques based on artificial intelligence for salivary biomarker discovery and validation in oral and maxillofacial diseases.

MXene-based photoacoustic transducer with a high-energy conversion efficiency.

The applications of two-dimensional transition metal carbide/nitride (MXene) in the fields of optoelectronics, sustainable energy, and sensors, among others, have been broadly investigated due to their special electrical, optical, and structural properties. In this Letter, MXene (Ti3C2Tx) has been firstly, to the best of our knowledge, adopted for the application of a photoacoustic transducer by taking advantage of the photothermal property. The efficiency of the photoacoustic transducer based on a sandwich structure of glass/MXene/polydimethylsiloxane (PDMS) has been experimentally demonstrated to be 1.25 × 10-2 by converting laser pulses into ultrasonic waves, generating a high acoustic pressure of 15.7 MPa without additional acoustic focusing. That can be explained by the great light absorption and photothermal conversion of the Ti3C2Tx layer.

Validity of nomograms for predicting cancer risk in oral leukoplakia and oral lichen planus.

OBJECTIVES: This study assessed the validity of nomograms for predicting malignant transformation (MT) among patients with oral leukoplakia (OL) and oral lichen planus (OLP). MATERIALS AND METHODS: Two nomograms were identified following a systematic search. Variables to interrogate both nomograms were obtained for a retrospective OL/OLP cohort. Then, the nomograms were applied to estimate MT probabilities twice and their average was used to calculate the discriminatory performance, calibration, and potential net benefit of the models. Subgroup analyses were performed for patients with OL, OLP, and oral epithelial dysplasia. RESULTS: Predicted probabilities were mostly significantly higher among OL/OLP patients who developed MT compared to those who did not (p = <0.001-0.034). AUC values and Brier scores of the nomograms were 0.644-0.844 and 0.040-0.088 among OL patients and 0.580-0.743 and 0.008-0.072 among OLP patients. Decision curve analysis suggested that the nomograms had some net benefit for risk stratification. However, the models did not best binary dysplasia grading in discriminatory validity and net benefit among patients with OL and oral epithelial dysplasia. CONCLUSION: Nomograms for predicting MT may have satisfactory validity among patients with OL than OLP, but they do not outperform binary dysplasia grading in risk stratification of OL.

Study and Treatment of Oral Squamous Cell Carcinoma-Insights and Perspectives.

The prevalence of oral squamous cell carcinoma (OSCC) has increased in recent decades, and its impact on the health system has become a new aspect [...].

A novel AIE material for sensing of Erythromycin in pure water by hydrogen bond in portable test strips and cellular imaging applications.

Erythromycin could be used to treat various bacterial infection, but it was harmful to the colonic microflora. Therefore, it is highly desirable to develop a fluorescence probe that could selectively and sensitively detect Erythromycin in pure water. In this work, a fluorescent probe named EHMC, which exhibited aggregation-induced emission (AIE) characteristic in solid state and water/EtOH binary solvent was developed for "turn on" sensing Erythromycin in pure water with high selectivity and sensitivity (detection limit: 1.78 × 10-8 M). Also, there are fewer interference from other antibiotics in the detection process of probe EHMC for Erythromycin. Moreover, probe EHMC could as a portable test strips for highly selective detection of Erythromycin and identification of different concentrations of Erythromycin. In addition, living cells imaging experiments displayed that probe EHMC could detect Erythromycin in A549 cells and BEAS-2B cells successfully. Combined with the theoretical calculation results The sensing mechanisms that the CO in Erythromycin and OH in EHMC formed intermolecular hydrogen bond and further formed new aggregates were confirmed by job' plot, 1H NMR, FT-IR, ESI-MS, DLS and TEM and DFT calculation.

Conformation Dependent Architectures of Assembled Antimicrobial Peptides with Enhanced Antimicrobial Ability.

Antimicrobial peptides (AMPs) are a developing class of natural and synthetic oligopeptides with host defense mechanisms against a broad spectrum of microorganisms. With in-depth research on the structural conformations of AMPs, synthesis or modification of peptides has shown great potential in effectively obtaining new therapeutic agents with improved physicochemical and biological properties. Notably, AMPs with self-assembled properties have gradually become a hot research topic for various biomedical applications. Compared to monomeric peptides, these peptides can exist in diverse forms (e.g., nanoparticles, nanorods, and nanofibers) and possess several advantages, such as high stability, good biocompatibility, and potent biological functions, after forming aggregates under specific conditions. In particular, the stability and antibacterial property of these AMPs can be modulated by rationally regulating the peptide sequences to promote self-assembly, leading to the reconstruction of molecular structure and spatial orientation while introducing some peptide fragments into the scaffolds. In this work, four self-assembled AMPs are developed, and the relationship between their chemical structures and antibacterial activity is explored extensively through different experiments. Importantly, the evaluation of antibacterial performance in both in vitro and in vivo studies has provided a general guide for using self-assembled AMPs in subsequent treatments for combating bacterial infections.