Electrolyte Additive l-Lysine Stabilizes the Zinc Electrode in Aqueous Zinc Batteries for Long Cycling Performance.

Rechargeable aqueous Zn-ion batteries (AZIBs) have been recognized as competitive devices for large-scale energy storage due to their characteristics of low cost, safe operation, and environmental friendliness. Nevertheless, their practical applications are greatly limited by zinc dendrite growth and side reactions occurring at the anode/electrolyte interface. Herein, we propose an effective and simple electrolyte engineering strategy, which is the introduction of l-lysine additive containing two amino groups and one carboxyl group into a ZnSO4 electrolyte to achieve stable and reversible Zn depositions. Theoretical calculations and experimental results reveal that the l-lysine can adsorb on the Zn anode surface due to the strong coordination effects between amino groups and Zn metal (Zn-N binding) and induce the reduction of ZnSO4 into inorganic ZnS, which can not only prevent interfacial side reactions but also regulate interfacial electric field on the zinc electrode surface to guide uniform Zn2+ electrodeposition to inhibit zinc dendrites. Consequently, the l-lysine additive in the electrolyte enables Zn||Zn symmetric cells to achieve an ultralong stable cycling up to 2400 h at 1 mA cm-2 with a low polarization of only about 16 mV and Zn||Cu asymmetric cells to obtain a high average Coulombic efficiency of 99.80% after stably cycling for more than 2000 h at 2 mA cm-2 (1 mAh cm-2). In addition, the Zn||MnO2@CNT full cell in an l-lysine-containing electrolyte also exhibits good cycling performance. This study offers a new perspective on multifunctional electrolyte additive for achieving highly reversible Zn metal anodes in AZIBs.

DrugMAP 2.0: molecular atlas and pharma-information of all drugs.

The escalating costs and high failure rates have decelerated the pace of drug development, which amplifies the research interests in developing combinatorial/repurposed drugs and understanding off-target adverse drug reaction (ADR). In other words, it is demanded to delineate the molecular atlas and pharma-information for the combinatorial/repurposed drugs and off-target interactions. However, such invaluable data were inadequately covered by existing databases. In this study, a major update was thus conducted to the DrugMAP, which accumulated (a) 20831 combinatorial drugs and their interacting atlas involving 1583 pharmacologically important molecules; (b) 842 repurposed drugs and their interacting atlas with 795 molecules; (c) 3260 off-targets relevant to the ADRs of 2731 drugs and (d) various types of pharmaceutical information, including diverse ADMET properties, versatile diseases, and various ADRs/off-targets. With the growing demands for discovering combinatorial/repurposed therapies and the rapidly emerging interest in AI-based drug discovery, DrugMAP was highly expected to act as an indispensable supplement to existing databases facilitating drug discovery, which was accessible at: https://idrblab.org/drugmap/.

A study on the impact of open source metaverse immersive teaching method on emergency skills training for medical undergraduate students.

BACKGROUND: In recent years, the traditional simulation-based medical teaching approach has faced challenges in meeting the requirements of practical emergency medicine education. This study utilized open-source tools and software to develop immersive panoramic videos using virtual reality technology for emergency medical teaching. It aims to investigate the efficacy of this novel teaching methodology. This transformation shifted the focus from physical simulation to virtual simulation in medical education, establishing a metaverse for emergency medical teaching. METHODS: In accordance with the curriculum guidelines, the instructors produced panoramic videos demonstrating procedures such as spinal injury management, humeral fracture with abdominal wall intestinal tube prolapse, head and chest composite injuries, cardiopulmonary resuscitation, and tracheal intubation. Using Unity software, a virtual training application for bronchoscopy was developed and integrated into the PICO4 VR all-in-one device to create a metaverse teaching environment. Fourth-year medical undergraduate students were allocated into either an experimental group (n = 26) or a control group (n = 30) based on student IDs. The experimental group received instruction through the metaverse immersive teaching method, while the control group followed the traditional simulation-based medical teaching approach. Both groups participated in theoretical and practical lessons as usual. Subsequently, all students underwent a four-station Objective Structured Clinical Examination (OSCE) to assess the effectiveness of the teaching methods based on their performance. Additionally, students in the experimental group provided subjective evaluations to assess their acceptance of the new teaching approach. RESULTS: Before the training commenced, there were no significant statistical differences in the first aid test scores between the experimental and control groups. Following the training, the experimental group outperformed the control group in the four-station OSCE examination, with all P-values being less than 0.05. The satisfaction rate among the experimental group regarding the new teaching method reached 88.46%, reflecting levels of satisfaction and extreme satisfaction. CONCLUSION: The open-source metaverse immersive teaching method has demonstrated a positive impact on enhancing the emergency skills of medical undergraduate students, with a high level of acceptance among students. In comparison to traditional simulated medical teaching methods, this approach requires less time and space, incurring lower costs, and is deemed worthy of wider adoption.

In Situ Hydroxide Growth over Nickel-Iron Phosphide with Enhanced Overall Water Splitting Performances.

In this work, three dimensional (3D) self-supported Ni-FeOH@Ni-FeP needle arrays with core-shell heterojunction structure are fabricated via in situ hydroxide growth over Ni-FeP surface. The as-prepared electrodes show an outstanding oxygen evolution reaction (OER) performance, only requiring the low overpotential of 232 mV to reach 200 mA cm-2 with the Tafel slop of 40 mV dec-1. For overall water splitting, an alkaline electrolyzer with these electrodes only requires a cell voltage of 2.14 V to reach 1 A cm-2. Mechanistic investigations for such excellent electrocatalytic performances are utilized by in situ Raman spectroscopy in conjunction with density functional theory (DFT) calculations. The computation results present that Ni-FeOH@Ni-FeP attains better intrinsic conductivity and the D-band center (close to that of the ideal catalyst), thus giving superior excellent catalytic performances. Likewise, the surface Ni-FeOH layer can improve the structural stability of Ni-FeP cores and attenuate the eventual formation of irreversible FeOOH products. More importantly, the appearance of FeOOH intermediates can effectively decrease the energy barrier of NiOOH intermediates, and then rapidly accelerate the sluggish reaction dynamics, as well as further enhance the electrocatalytic activities, reversibility and cycling stability.

FERREG: ferroptosis-based regulation of disease occurrence, progression and therapeutic response.

Ferroptosis is a non-apoptotic, iron-dependent regulatory form of cell death characterized by the accumulation of intracellular reactive oxygen species. In recent years, a large and growing body of literature has investigated ferroptosis. Since ferroptosis is associated with various physiological activities and regulated by a variety of cellular metabolism and mitochondrial activity, ferroptosis has been closely related to the occurrence and development of many diseases, including cancer, aging, neurodegenerative diseases, ischemia-reperfusion injury and other pathological cell death. The regulation of ferroptosis mainly focuses on three pathways: system Xc-/GPX4 axis, lipid peroxidation and iron metabolism. The genes involved in these processes were divided into driver, suppressor and marker. Importantly, small molecules or drugs that mediate the expression of these genes are often good treatments in the clinic. Herein, a newly developed database, named 'FERREG', is documented to (i) providing the data of ferroptosis-related regulation of diseases occurrence, progression and drug response; (ii) explicitly describing the molecular mechanisms underlying each regulation; and (iii) fully referencing the collected data by cross-linking them to available databases. Collectively, FERREG contains 51 targets, 718 regulators, 445 ferroptosis-related drugs and 158 ferroptosis-related disease responses. FERREG can be accessed at https://idrblab.org/ferreg/.

Less is More: Underlying Mechanism of Zn Electrode Long-Term Stability using Sodium L-Ascorbate as Electrolyte Additive.

Structured passivation layers and hydrated Zn2+ solvation structure strongly influence Zn depositions on Zn electrodes and then the cycle life and electrochemical performance of aqueous zinc ion batteries. To achieve these, the electrolyte additive of sodium L-ascorbate (Ass) is introduced into aqueous zinc sulfate (ZnSO4, ZS) electrolyte solutions. Combined experimental characterizations with theoretical calculations, the unique passivation layers with vertical arrayed micro-nano structure are clearly observed, as well as the hydrated Zn2+ solvation structure is changed by replacing two ligand water molecules with As-, thus regulating the wettability and interfacial electric field intensity of Zn surfaces, facilitating rapid ionic diffusions within electrolytes and electrodes together with the inhibited side reactions and uniform depositions of Zn2+. When tested in Zn||Zn symmetric cell, the electrolyte containing Ass is extraordinarily stably operated for the long time ≈3700 h at both 1 mA cm-2 and 1 mAh cm-2. In Zn||MnO2 full coin cells, the energy density can still maintain as high as ≈184 Wh kg-1 at the power density high up to 2 kW kg-1, as well as the capacity retention can reach up to 80.5% even after 1000 cycles at 2 A g-1, which are substantially superior to the control cells.

VARIDT 3.0: the phenotypic and regulatory variability of drug transporter.

The phenotypic and regulatory variability of drug transporter (DT) are vital for the understanding of drug responses, drug-drug interactions, multidrug resistances, and so on. The ADME property of a drug is collectively determined by multiple types of variability, such as: microbiota influence (MBI), transcriptional regulation (TSR), epigenetics regulation (EGR), exogenous modulation (EGM) and post-translational modification (PTM). However, no database has yet been available to comprehensively describe these valuable variabilities of DTs. In this study, a major update of VARIDT was therefore conducted, which gave 2072 MBIs, 10 610 TSRs, 46 748 EGRs, 12 209 EGMs and 10 255 PTMs. These variability data were closely related to the transportation of 585 approved and 301 clinical trial drugs for treating 572 diseases. Moreover, the majority of the DTs in this database were found with multiple variabilities, which allowed a collective consideration in determining the ADME properties of a drug. All in all, VARIDT 3.0 is expected to be a popular data repository that could become an essential complement to existing pharmaceutical databases, and is freely accessible without any login requirement at: https://idrblab.org/varidt/.

INTEDE 2.0: the metabolic roadmap of drugs.

The metabolic roadmap of drugs (MRD) is a comprehensive atlas for understanding the stepwise and sequential metabolism of certain drug in living organisms. It plays a vital role in lead optimization, personalized medication, and ADMET research. The MRD consists of three main components: (i) the sequential catalyses of drug and its metabolites by different drug-metabolizing enzymes (DMEs), (ii) a comprehensive collection of metabolic reactions along the entire MRD and (iii) a systematic description on efficacy & toxicity for all metabolites of a studied drug. However, there is no database available for describing the comprehensive metabolic roadmaps of drugs. Therefore, in this study, a major update of INTEDE was conducted, which provided the stepwise & sequential metabolic roadmaps for a total of 4701 drugs, and a total of 22 165 metabolic reactions containing 1088 DMEs and 18 882 drug metabolites. Additionally, the INTEDE 2.0 labeled the pharmacological properties (pharmacological activity or toxicity) of metabolites and provided their structural information. Furthermore, 3717 drug metabolism relationships were supplemented (from 7338 to 11 055). All in all, INTEDE 2.0 is highly expected to attract broad interests from related research community and serve as an essential supplement to existing pharmaceutical/biological/chemical databases. INTEDE 2.0 can now be accessible freely without any login requirement at: http://idrblab.org/intede/.

Decoding Drug Response with Structurized Gridding Map-based Cell Representation.

A thorough understanding of cell-line drug response mechanisms is crucial for drug development, repurposing, and resistance reversal. While targeted anticancer therapies have shown promise, not all cancers have well-established biomarkers to stratify drug response. Single-gene associations only explain a small fraction of the observed drug sensitivity, so a more comprehensive method is needed. However, while deep learning models have shown promise in predicting drug response in cell lines, they still face significant challenges when it comes to their application in clinical applications. Therefore, this study proposed a new strategy called DD-Response for cell-line drug response prediction. First, a limitation of narrow modeling horizons was overcome to expand the model training domain by integrating multiple datasets through source-specific label binarization. Second, a modified representation based on a two-dimensional structurized gridding map (SGM) was developed for cell lines & drugs, avoiding feature correlation neglect and potential information loss. Third, a dual-branch, multi-channel convolutional neural network-based model for pairwise response prediction was constructed, enabling accurate outcomes and improved exploration of underlying mechanisms. As a result, the DD-Response demonstrated superior performance, captured cell-line characteristic variations, and provided insights into key factors impacting cell-line drug response. In addition, DD-Response exhibited scalability in predicting clinical patient responses to drug therapy. Overall, because of DD-response's excellent ability to predict drug response and capture key molecules behind them, DD-response is expected to greatly facilitate drug discovery, repurposing, resistance reversal, and therapeutic optimization.

A comparison of maxillofacial growth in Chinese children with isolated cleft palate treated with two different palatoplasty techniques without relaxing incisions: a preliminary study.

OBJECTIVE: To assess the maxillofacial growth of patients with isolated cleft palate following the Sommerlad-Furlow modified technique and compare it with the effect of the Sommerlad technique. STUDY DESIGN: A Retrospective Cohort Study. METHODS: A total of 90 participants, 60 patients with non-syndromic isolated soft and hard cleft palate (ISHCP) underwent primary palatoplasty without relaxing incision (30 patients received the Sommerlad-Furlow modified (S-F) technique and 30 received Sommerlad (S) technique). While the other 30 were healthy noncleft participants with skeletal class I pattern (C group). All participants had lateral cephalometric radiographs at least 5 years old age. All the study variables were measured by using stable landmarks, including 11 linear and 9 angular variants. RESULTS: The means age at collection of cephalograms were 6.03 ± 0.80 (5-7 yrs) in the S group, 5.96 ± 0.76 (5-7 yrs) in the S-F group, and 5.91 ± 0.87 (5-7 yrs) in the C group. Regarding cranial base, the results showed that there were no statistically significant differences between the three groups in S-N and S-N-Ba. The S group had a significantly shortest S-Ba than the S-F & C groups (P = 0.01), but there was no statistically significant difference between S-F and C groups (P = 0.80). Regarding skeletal maxillary growth, the S group had significantly shorter Co-A, S- PM and significantly less SNA angle than the C group (P = < 0.01). While there was no significant difference between S-F & C groups (P = 0.42). The S group had significantly more MP-SN inclination than the C group (P = < 0.01). Regarding skeletal mandibular growth, there were no statistically significant differences in all linear and angular mandibular measurements between the three groups, except Co-Gn of the S group had a significantly shorter length than the C group (P = 0.05). Regarding intermaxillary relation, the S-F group had no significant differences in Co-Gn-Co-A and ANB as compared with the C group. The S group had significantly less ANB angle than S-F & C groups (P = 0.01 & P = < 0.01). In addition, there were no significant differences in all angular occlusal measurements between the three groups. CONCLUSION: As a preliminary report, Sommerlad-Furlow modified technique showed that maxillary positioning in the face tended to be better, and the intermaxillary relationship was more satisfactory than that in Sommerlad technique when compared them in healthy noncleft participants.

Impact of relaxing incisions on maxillofacial growth following Sommerlad-Furlow modified technique in patients with isolated cleft palate: a preliminary comparative study.

OBJECTIVE: To estimate the impact of relaxing incisions on maxillofacial growth following Sommerlad-Furlow modified technique in patients with isolated cleft palate. STUDY DESIGN: A Retrospective Cohort Study. METHODS: A total of 90 participants, 60 patients with non-syndromic isolated soft and hard cleft palate underwent primary palatoplasty (30 patients received the Sommerlad-Furlow modified technique without relaxing incision (S.F-RI group), and 30 received Sommerlad-Furlow modified technique with relaxing (S.F+RI group) with no significant difference found between them regarding the cleft type, cleft width, and age at repair. While the other 30 were healthy noncleft participants with skeletal class I pattern as a Control group. The control group (C group) was matched with the patient groups in number, age, and sex. All participants had lateral cephalometric radiographs at least 5 years old age. The lateral cephalometric radiographs were taken with the same equipment by the same experienced radiologist while the participants were in centric occlusion and a standardized upright position, with the transporionic axis and Frankfort horizontal plane parallel to the surface of the floor. A well-trained assessor (S. Elayah) used DOLPHIN Imaging Software to trace twice to eliminate measurement errors. All the study variables were measured using stable landmarks, including 12 linear and 10 angular variants. RESULTS: The mean age at collection of cephalograms was 6.03 ± 0.80 in the S.F+RI group, 5.96 ± 0.76 in the S.F-RI group, and 5.91 ± 0.87 in the C group. Regarding cranial base, the results showed no statistically significant differences between the three groups in S-N and S-N-Ba. While the S.F+R.I group had a significantly shortest S-Ba than the S.F-R.I & C groups (P = 0.01 & P < 0.01), but there was no statistically significant difference between S.F-R.I & C groups (P = 0.71). Regarding the skeletal maxilla, there was no significant difference between the S.F+R.I and S.F-R.I groups in all linear measurements (N-ANS and S-PM) except Co-A, the S.F+R.I group had significantly shorter Co-A than the S.F-R.I & C groups (P = < 0.01). While the angular measurement, S.F+R.I group had significantly less SNA angle than the S.F-R.I & C groups (P = < 0.01). Regarding mandibular bone, there were no statistically significant differences in all linear and angular mandibular measurements between the S.F+R.I and S.F-R.I.groups. Regarding intermaxillary relation, the S.F+R.I group had significant differences in Co-Gn-Co-A and ANB compared to the S.F-R.I & C groups (P = < 0.01). While there was no statistically significant difference in PP-MP between the three groups. CONCLUSION: As a preliminary report, the Sommerlad-Furlow modified technique without relaxing incisions was found to have a good maxillary positioning in the face and a satisfactory intermaxillary relationship compared to the Sommerlad-Furlow modified technique with relaxing incisions.

Current insights in the preclinical study of palatal wound healing and oronasal fistula after cleft palate repair.

Poor palatal wound healing after cleft palate repair could lead to unfavorable prognosis such as oronasal fistula (ONF), which might affect the patient's velopharyngeal function as well as their quality of life. Thus, restoring poor palatal wound healing for avoiding the occurrence of ONF should be considered the key to postoperative care after cleft palate repair. This review provided current insights in the preclinical study of poor palatal wound healing after cleft palate repair. This review comprehensively introduced the animal model establishment for palatal wound healing and related ONF, including the models by mice, rats, piglets, and dogs, and then demonstrated the aspects for investigating poor palatal wound healing and related treatments, including possible signaling pathways that could be involved in the formation of poor palatal wound healing, the related microbiota changes because of the deformity of palatal structure, and the studies for potential therapeutic strategies for palatal wound healing and ONF. The purpose of this review was to show the state of the art in preclinical studies about palatal wound healing after cleft palate repair and to show the promising aspects for better management of palatal wound healing.

Establishment of an Oronasal Fistula Mice Model.

This study presents a method utilizing heated ophthalmologic cautery to develop a viable model for investigating oronasal fistulas. C57BL/6 mice were used to establish the oronasal fistula (ONF) model. To create the ONF, the mice were anesthetized, immobilized, and their hard palates were exposed. During the surgical procedure, a 2.0 x 1.5 mm full-thickness mucosal injury was induced in the midline of the hard palate using ophthalmologic cautery. It was crucial to control the size of the ONF and minimize bleeding in order to ensure the success of the experiment. Verification of the ONF model's effectiveness was conducted on the 7th-day post-operation, encompassing both anatomical and functional assessments. The presence of the nasal septum within the oral cavity and the outflow of sterile water from the nostrils upon injection into the oral cavity confirmed the successful establishment of the ONF model. The model demonstrated a practical and successful oronasal fistula, characterized by a low mortality rate, significant weight changes, and minimal variation in ONF size. Future studies may consider adopting this methodology to elucidate the mechanisms of palate wound healing and explore novel treatments for oronasal fistulas.

Early-life noise exposure causes cognitive impairment in a sex-dependent manner by disrupting homeostasis of the microbiota-gut-brain axis.

Epidemiological investigations show that noise exposure in early life is associated with health and cognitive impairment. The gut microbiome established in early life plays a crucial role in modulating developmental processes that subsequently affect brain function and behavior. Here, we examined the impact of early-life exposure to noise on cognitive function in adolescent rats by analyzing the gut microbiome and metabolome to elucidate the underlying mechanisms. Chronic noise exposure during early life led to cognitive deficits, hippocampal injury, and neuroinflammation. Early-life noise exposure showed significant difference on the composition and function of the gut microbiome throughout adolescence, subsequently causing axis-series changes in fecal short-chain fatty acid (SCFA) metabolism and serum metabolome profiles, as well as dysregulation of endothelial tight junction proteins, in both intestine and brain. We also observed sex-dependent effects of microbiota depletion on SCFA-related beneficial bacteria in adolescence. Experiments on microbiota transplantation and SCFA supplementation further confirmed the role of intestinal bacteria and related SCFAs in early-life noise-exposure-induced impairments in cognition, epithelial integrity, and neuroinflammation. Overall, these results highlight the homeostatic imbalance of microbiota-gut-brain axis as an important physiological response toward environmental noise during early life and reveals subtle differences in molecular signaling processes between male and female rats.

Heterodimerization of Human UDP-Glucuronosyltransferase 1A9 and UDP-Glucuronosyltransferase 2B7 Alters Their Glucuronidation Activities.

Human UDP-glucuronosyltransferases (UGTs) play a pivotal role as prominent phase II metabolic enzymes, mediating the glucuronidation of both endobiotics and xenobiotics. Dimerization greatly modulates the enzymatic activities of UGTs. In this study, we examined the influence of three mutations (H35A, H268Y, and N68A/N315A) and four truncations (signal peptide, single transmembrane helix, cytosolic tail, and di-lysine motif) in UGT2B7 on its heterodimerization with wild-type UGT1A9, using a Bac-to-Bac expression system. We employed quantitative fluorescence resonance energy transfer (FRET) techniques and co-immunoprecipitation assays to evaluate the formation of heterodimers between UGT1A9 and UGT2B7 allozymes. Furthermore, we evaluated the glucuronidation activities of the heterodimers using zidovudine and propofol as substrates for UGT2B7 and UGT1A9, respectively. Our findings revealed that the histidine residue at codon 35 was involved in the dimeric interaction, as evidenced by the FRET efficiencies and catalytic activities. Interestingly, the signal peptide and single transmembrane helix domain of UGT2B7 had no impact on the protein-protein interaction. These results provide valuable insights for a comprehensive understanding of UGT1A9/UGT2B7 heterodimer formation and its association with glucuronidation activity. SIGNIFICANCE STATEMENT: Our findings revealed that the H35A mutation in UGT2B7 affected the affinity of protein-protein interaction, leading to discernable variations in fluorescence resonance energy transfer efficiencies and catalytic activity. Furthermore, the signal peptide and single transmembrane helix domain of UGT2B7 did not influence heterodimer formation. These results provide valuable insights into the combined effects of polymorphisms and protein-protein interactions on the catalytic activity of UGT1A9 and UGT2B7, enhancing our understanding of UGT dimerization and its impact on metabolite formation.

Thioredoxin-1 inhibits the activation of IRE1 by targeting Hsp90/p-Cdc37 chaperone complex in Parkinson disease.

Endoplasmic reticulum stress is implicated in the etiopathogenesis of Parkinson disease (PD). Our previous study has revealed that thioredoxin-1 (Trx-1) attenuated IRE1 activation in 1-methyl-4-phenylpyridinium ion (MPP+)/1-methy-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced PD models. However, its exact mechanism has been largely unclear. In this research, it was reported for the first time that the protein levels of heat shock protein 90 (Hsp90) and phosphorylated cell division cycle 37 (p-Cdc37) were significantly decreased and the interaction of Hsp90/p-Cdc37 complex with IRE1 was disturbed in MPP+/MPTP-induced PD models. Trx-1 overexpression reversed the expression of Hsp90 and p-Cdc37 in cultured cells and the substantia nigra pars compacta of mice. More importantly, Trx-1 overexpression enhanced the interaction of Hsp90/p-Cdc37 complex with IRE1. In conclusion, our data demonstrated that Trx-1 inhibited IRE1 activation in PD by elevating the expression of Hsp90 and p-Cdc37 and strengthening the interaction of Hsp90/p-Cdc37 complex and IRE1.

ChatGPT for shaping the future of dentistry: the potential of multi-modal large language model.

The ChatGPT, a lite and conversational variant of Generative Pretrained Transformer 4 (GPT-4) developed by OpenAI, is one of the milestone Large Language Models (LLMs) with billions of parameters. LLMs have stirred up much interest among researchers and practitioners in their impressive skills in natural language processing tasks, which profoundly impact various fields. This paper mainly discusses the future applications of LLMs in dentistry. We introduce two primary LLM deployment methods in dentistry, including automated dental diagnosis and cross-modal dental diagnosis, and examine their potential applications. Especially, equipped with a cross-modal encoder, a single LLM can manage multi-source data and conduct advanced natural language reasoning to perform complex clinical operations. We also present cases to demonstrate the potential of a fully automatic Multi-Modal LLM AI system for dentistry clinical application. While LLMs offer significant potential benefits, the challenges, such as data privacy, data quality, and model bias, need further study. Overall, LLMs have the potential to revolutionize dental diagnosis and treatment, which indicates a promising avenue for clinical application and research in dentistry.

Development of postoperative velopharyngeal function in patients with cleft palate.

OBJECTIVE: Patients with a cleft palate often experience a velopharyngeal dysfunction known as velopharyngeal insufficiency (VPI). The purpose of this study was to examine the development of velopharyngeal function (VPF) following primary palatoplasty and the factors that are linked to it. METHODS: A retrospective study was conducted to examine the medical records of patients who had cleft palate, with or without cleft lip (CP ± L) and underwent palatoplasty at a Tertiary Affiliated Hospital between 2004 and 2017. Postoperative evaluation of VPF was conducted at two follow-up times (T1, T2) and was classified as either normal VPF, mild VPI, or moderate/severe VPI. The consistency of VPF evaluations between the two time points was then assessed, and patients were categorized into either the consistent or inconsistent group. The study collected and analyzed data on gender, cleft type, age at operation, follow-up duration, and speech records. RESULTS: The study included 188 patients with CP ± L. Out of these, 138 patients (73.4%) showed consistent VPF evaluations, while 50 patients (26.6%) showed inconsistent VPF evaluations. Among those with VPI at T1 (91 patients), 36 patients (39.6%) had normal VPF at T2. The rate of VPI decreased from 48.40% at T1 to 27.13% at T2, whereas the rate of normal VPF increased from 44.68% at T1 to 68.09% at T2. The consistent group had a significantly younger age at operation (2.90 ± 3.82 vs 3.68 ± 4.02), a longer duration of T1 (1.67 ± 0.97 vs 1.04 ± 0.59), and a lower comprehensive score of speech performance (1.86 ± 1.27 vs 2.60 ± 1.07) than the inconsistent group. CONCLUSIONS: It has been verified that there are changes in the development of VPF over time. Patients who underwent palatoplasty at a younger age were more likely to have confirmed VPF diagnosis at the first evaluation. The duration of follow-up was identified as a critical factor that affects the confirmation of VPF diagnosis.

Lactobacillus rhamnosus GG ameliorates noise-induced cognitive deficits and systemic inflammation in rats by modulating the gut-brain axis.

Background: Environmental noise exposure is linked to neuroinflammation and imbalance of the gut microbiota. Promoting gut microbiota homeostasis may be a key factor in relieving the deleterious non-auditory effects of noise. This study aimed to investigate the effect of Lactobacillus rhamnosus GG (LGG) intervention on noise-induced cognitive deficits and systemic inflammation in rats. Methods: Learning and memory were assessed using the Morris water maze, while 16S rRNA sequencing and gas chromatography-mass spectrometry were used to analyze the gut microbiota and short-chain fatty acid (SCFA) content. Endothelial tight junction proteins and serum inflammatory mediators were assessed to explore the underlying pathological mechanisms. Results: The results indicated that Lactobacillus rhamnosus GG intervention ameliorated noise-induced memory deterioration, promoted the proliferation of beneficial bacteria, inhibited the growth of harmful bacteria, improved dysregulation of SCFA-producing bacteria, and regulated SCFA levels. Mechanistically, noise exposure led to a decrease in tight junction proteins in the gut and hippocampus and an increase in serum inflammatory mediators, which were significantly alleviated by Lactobacillus rhamnosus GG intervention. Conclusion: Taken together, Lactobacillus rhamnosus GG intervention reduced gut bacterial translocation, restored gut and blood-brain barrier functions, and improved gut bacterial balance in rats exposed to chronic noise, thereby protecting against cognitive deficits and systemic inflammation by modulating the gut-brain axis.

State-of-the-art Application of Artificial Intelligence to Transporter-centered Functional and Pharmaceutical Research.

Protein transporters not only have essential functions in regulating the transport of endogenous substrates and remote communication between organs and organisms, but they also play a vital role in drug absorption, distribution, and excretion and are recognized as major determinants of drug safety and efficacy. Understanding transporter function is important for drug development and clarifying disease mechanisms. However, the experimental-based functional research on transporters has been challenged and hinged by the expensive cost of time and resources. With the increasing volume of relevant omics datasets and the rapid evolution of artificial intelligence (AI) techniques, next-generation AI is becoming increasingly prevalent in the functional and pharmaceutical research of transporters. Thus, a comprehensive discussion on the state-of-the-art application of AI in three cutting-edge directions was provided in this review, which included (a) transporter classification and function annotation, (b) structure discovery of membrane transporters, and (c) drug-transporter interaction prediction. This study provides a panoramic view of AI algorithms and tools applied to the field of transporters. It is expected to guide a better understanding and utilization of AI techniques for in-depth studies of transporter-centered functional and pharmaceutical research.