Large animal models for Huntington's disease research

Huntington'sdisease(HD)isahereditary neurodegenerative disorder for which there is currently no effectivetreatmentavailable.Consequently,the development of appropriate disease models is critical to thoroughly investigate disease progression.The genetic basis of HD involves the abnormal expansion of CAG repeats in the huntingtin(HTT)gene,leading to the expansion of a polyglutamine repeat in the HTT protein.Mutant HTT carrying the expanded polyglutamine repeat undergoes misfolding and forms aggregates in the brain,which precipitate selective neuronal loss in specific brain regions.Animal models play an important role in elucidating the pathogenesis of neurodegenerative disorders such as HD and in identifying potential therapeutic targets.Due to the marked species differences between rodents and larger animals,substantial efforts have been directed toward establishing large animal models for HD research.These models are pivotal for advancing the discovery of novel therapeutic targets,enhancing effective drug delivery methods,and improving treatment outcomes.We have explored the advantages of utilizing large animal models,particularly pigs,in previous reviews.Since then,however,significant progress has been made in developing more sophisticated animal models that faithfully replicate the typical pathology of HD.In the current review,we provide a comprehensive overview of large animal models of HD,incorporating recent findings regarding the establishment of HD knock-in(KI)pigs and their genetic therapy.We also explore the utilization of large animal models in HD research,with a focus on sheep,non-human primates(NHPs),and pigs.Our objective is to provide valuable insights into the application of these large animal models for the investigation and treatment of neurodegenerative disorders.

Frontogenesis and Frontolysis of a Cold Filament Driven by the Cross-Filament Wind and Wave Fields Simulated by a Large Eddy Simulation

The variations of the frontogenetic trend of a cold filament induced by the cross-filament wind and wave fields are studied by a non-hydrostatic large eddy simulation. Five cases with different strengths of wind and wave fields are studied.The results show that the intense wind and wave fields further break the symmetries of submesoscale flow fields and suppress the levels of filament frontogenesis. The changes of secondary circulation directions—that is, the conversion between the convergence and divergence of the surface cross-filament currents with the downwelling and upwelling jets in the filament center—are associated with the inertial oscillation. The filament frontogenesis and frontolysis caused by the changes of secondary circulation directions may periodically sharpen and smooth the gradient of submesoscale flow fields.The lifecycle of the cold filament may include multiple stages of filament frontogenesis and frontolysis.

Shallow Convection Dataset Simulated by Three Different Large Eddy Models

Shallow convection plays an important role in transporting heat and moisture from the near-surface to higher altitudes,yet its parameterization in numerical models remains a great challenge,partly due to the lack of high-resolution observations.This study describes a large eddy simulation(LES)dataset for four shallow convection cases that differ primarily in inversion strength,which can be used as a surrogate for real data.To reduce the uncertainty in LES modeling,three different large eddy models were used,including SAM(System for Atmospheric Modeling),WRF(Weather Research and Forecasting model),and UCLA-LES.Results show that the different models generally exhibit similar behavior for each shallow convection case,despite some differences in the details of the convective structure.In addition to grid-averaged fields,conditionally sampled variables,such as in-cloud moisture and vertical velocity,are also provided,which are indispensable for calculation of the entrainment/detrainment rate.Considering the essentiality of the entraining/detraining process in the parameterization of cumulus convection,the dataset presented in this study is potentially useful for validation and improvement of the parameterization of shallow convection.

Computing large deviation prefactors of stochastic dynamical systems based on machine learning

We present a large deviation theory that characterizes the exponential estimate for rare events in stochastic dynamical systems in the limit of weak noise.We aim to consider a next-to-leading-order approximation for more accurate calculation of the mean exit time by computing large deviation prefactors with the aid of machine learning.More specifically,we design a neural network framework to compute quasipotential,most probable paths and prefactors based on the orthogonal decomposition of a vector field.We corroborate the higher effectiveness and accuracy of our algorithm with two toy models.Numerical experiments demonstrate its powerful functionality in exploring the internal mechanism of rare events triggered by weak random fluctuations.

Multi-environment BSA-seq using large F3 populations is able to achieve reliable QTL mapping with high power and resolution: An experimental demonstration in rice

Bulked-segregant analysis by deep sequencing(BSA-seq) is a widely used method for mapping QTL(quantitative trait loci) due to its simplicity, speed, cost-effectiveness, and efficiency. However, the ability of BSA-seq to detect QTL is often limited by inappropriate experimental designs, as evidenced by numerous practical studies. Most BSA-seq studies have utilized small to medium-sized populations, with F2populations being the most common choice. Nevertheless, theoretical studies have shown that using a large population with an appropriate pool size can significantly enhance the power and resolution of QTL detection in BSA-seq, with F_(3)populations offering notable advantages over F2populations. To provide an experimental demonstration, we tested the power of BSA-seq to identify QTL controlling days from sowing to heading(DTH) in a 7200-plant rice F_(3)population in two environments, with a pool size of approximately 500. Each experiment identified 34 QTL, an order of magnitude greater than reported in most BSA-seq experiments, of which 23 were detected in both experiments, with 17 of these located near41 previously reported QTL and eight cloned genes known to control DTH in rice. These results indicate that QTL mapping by BSA-seq in large F_(3)populations and multi-environment experiments can achieve high power, resolution, and reliability.

THE OPTIMAL LARGE TIME BEHAVIOR OF 3D QUASILINEAR HYPERBOLIC EQUATIONS WITH NONLINEAR

We are concerned with the large-time behavior of 3D quasilinear hyperbolic equations with nonlinear damping.The main novelty of this paper is two-fold.First,we prove the optimal decay rates of the second and third order spatial derivatives of the solution,which are the same as those of the heat equation,and in particular,are faster than ones of previous related works.Second,for well-chosen initial data,we also show that the lower optimal L^(2) convergence rate of the k(∈[0,3])-order spatial derivatives of the solution is(1+t)^(-(2+2k)/4).Therefore,our decay rates are optimal in this sense.The proofs are based on the Fourier splitting method,low-frequency and high-frequency decomposition,and delicate energy estimates.

The Turbulent Schmidt Number for Transient Contaminant Dispersion in a Large Ventilated Room Using a Realizable k-εModel

Buildings with large open spaces in which chemicals are handled are often exposed to the risk of explosions.Computational fluid dynamics is a useful and convenient way to investigate contaminant dispersion in such large spaces.The turbulent Schmidt number(Sc_(t))concept has typically been used in this regard,and most studies have adopted a default value.We studied the concentration distribution for sulfur hexafluoride(SF_(6))assuming different emission rates and considering the effect of Sc_(t).Then we examined the same problem for a light gas by assuming hydrogen gas(H_(2))as the contaminant.When SF_(6) was considered as the contaminant gas,a variation in the emission rate completely changed the concentration distribution.When the emission rate was low,the gravitational effect did not take place.For both low and high emission rates,an increase in S_(ct) accelerated the transport rate of SF_(6).In contrast,for H_(2) as the contaminant gas,a larger S_(ct) could induce a decrease in the H_(2) transport rate.

Multi-blade rubbing characteristics of the shaft-disk-blade-casing system with large rotation

Blade rubbing faults cause detrimental impact on the operation of aeroengines. Most of the existing studies on blade rubbing in the shaft-disk-blade-casing(SDBC) system have overlooked the elastic deformation of the blade, while some only consider the whirl of the rotor, neglecting its spin. To address these limitations, this paper proposes a dynamic model with large rotation for the SDBC system. The model incorporates the spin and whirl of the rotor, enabling the realistic reproduction of multiblade rubbing faults. To verify the accuracy of the SDBC model with large rotation and demonstrate its capability to effectively consider the rotational effects such as the centrifugal stiffening and gyroscopic effects, the natural characteristics and dynamic responses of the proposed model are compared with those obtained from reported research and experimental results. Furthermore, the effects of the rotating speed, contact stiffness,and blade number on the dynamic characteristics of the SDBC system with multi-blade rubbing are investigated. The results indicate that the phase angle between the rotor deflection and the unbalance excitation force increases with the increasing rotating speed,which significantly influences the rubbing penetration of each blade. The natural frequency of the SDBC system with rubbing constrain can be observed in the acceleration response of the casing and the torsional response of the shaft, and the frequency is related to the contact stiffness. Moreover, the vibration amplitude increases significantly with the product of the blade number under rubbing, and the rotating frequency approaches the natural frequency of the SDBC system. The proposed model can provide valuable insight for the fault diagnosis of rubbing in bladed rotating machinery.

Topology Optimization of Metamaterial Microstructures for Negative Poisson’s Ratio under Large Deformation Using a Gradient-Free Method

Negative Poisson’s ratio(NPR)metamaterials are attractive for their unique mechanical behaviors and potential applications in deformation control and energy absorption.However,when subjected to significant stretching,NPR metamaterials designed under small strain assumption may experience a rapid degradation in NPR performance.To address this issue,this study aims to design metamaterials maintaining a targeted NPR under large deformation by taking advantage of the geometry nonlinearity mechanism.A representative periodic unit cell is modeled considering geometry nonlinearity,and its topology is designed using a gradient-free method.The unit cell microstructural topologies are described with the material-field series-expansion(MFSE)method.The MFSE method assumes spatial correlation of the material distribution,which greatly reduces the number of required design variables.To conveniently design metamaterials with desired NPR under large deformation,we propose a two-stage gradient-free metamaterial topology optimization method,which fully takes advantage of the dimension reduction benefits of the MFSE method and the Kriging surrogate model technique.Initially,we use homogenization to find a preliminary NPR design under a small deformation assumption.In the second stage,we begin with this preliminary design and minimize deviations in NPR from a targeted value under large deformation.Using this strategy and solution technique,we successfully obtain a group of NPR metamaterials that can sustain different desired NPRs in the range of[−0.8,−0.1]under uniaxial stretching up to 20% strain.Furthermore,typical microstructure designs are fabricated and tested through experiments.The experimental results show good consistency with our numerical results,demonstrating the effectiveness of the present gradientfree NPR metamaterial design strategy.

Customized scaffolds for large bone defects using 3D‑printed modular blocks from 2D‑medical images

Additive manufacturing(AM)has revolutionized the design and manufacturing of patient-specific,three-dimensional(3D),complex porous structures known as scaffolds for tissue engineering applications.The use of advanced image acquisition techniques,image processing,and computer-aided design methods has enabled the precise design and additive manufacturing of anatomically correct and patient-specific implants and scaffolds.However,these sophisticated techniques can be timeconsuming,labor-intensive,and expensive.Moreover,the necessary imaging and manufacturing equipment may not be readily available when urgent treatment is needed for trauma patients.In this study,a novel design and AM methods are proposed for the development of modular and customizable scaffold blocks that can be adapted to fit the bone defect area of a patient.These modular scaffold blocks can be combined to quickly form any patient-specific scaffold directly from two-dimensional(2D)medical images when the surgeon lacks access to a 3D printer or cannot wait for lengthy 3D imaging,modeling,and 3D printing during surgery.The proposed method begins with developing a bone surface-modeling algorithm that reconstructs a model of the patient’s bone from 2D medical image measurements without the need for expensive 3D medical imaging or segmentation.This algorithm can generate both patient-specific and average bone models.Additionally,a biomimetic continuous path planning method is developed for the additive manufacturing of scaffolds,allowing porous scaffold blocks with the desired biomechanical properties to be manufactured directly from 2D data or images.The algorithms are implemented,and the designed scaffold blocks are 3D printed using an extrusion-based AM process.Guidelines and instructions are also provided to assist surgeons in assembling scaffold blocks for the self-repair of patient-specific large bone defects.

Enhancing Relational Triple Extraction in Specific Domains:Semantic Enhancement and Synergy of Large Language Models and Small Pre-Trained Language Models

In the process of constructing domain-specific knowledge graphs,the task of relational triple extraction plays a critical role in transforming unstructured text into structured information.Existing relational triple extraction models facemultiple challenges when processing domain-specific data,including insufficient utilization of semantic interaction information between entities and relations,difficulties in handling challenging samples,and the scarcity of domain-specific datasets.To address these issues,our study introduces three innovative components:Relation semantic enhancement,data augmentation,and a voting strategy,all designed to significantly improve the model’s performance in tackling domain-specific relational triple extraction tasks.We first propose an innovative attention interaction module.This method significantly enhances the semantic interaction capabilities between entities and relations by integrating semantic information fromrelation labels.Second,we propose a voting strategy that effectively combines the strengths of large languagemodels(LLMs)and fine-tuned small pre-trained language models(SLMs)to reevaluate challenging samples,thereby improving the model’s adaptability in specific domains.Additionally,we explore the use of LLMs for data augmentation,aiming to generate domain-specific datasets to alleviate the scarcity of domain data.Experiments conducted on three domain-specific datasets demonstrate that our model outperforms existing comparative models in several aspects,with F1 scores exceeding the State of the Art models by 2%,1.6%,and 0.6%,respectively,validating the effectiveness and generalizability of our approach.

The influence of inter-band rock on rib spalling in longwall panel with large mining height

In order to improve rib stability,failure criteria and instability mode of a thick coal seam with inter-band rock layer are analysed in this study.A three-dimensional mechanical model is established for the rib by considering the rock layer.A safety factor is defined foy the rib,and it is observed that the safety factor exhibits a positive correlation with the thickness and strength of the inter-band rock.A calculation method for determining critical parameters of the rock layer is presented to ensure the rib stability.It is revealed that incomplete propagation of the fracture at the hard rock constitutes a fundamental prerequisite for ensuring the rib stability.The influence of the position of the inter-band rock in the coal seam on failure mechanism of the rib was thoroughly investigated by developing a series of physical models for the rib at the face area.The best position for the inter-band rock in the coal seam is at a height of 1.5 m away from the roof line,which tends to provide a good stability state for the rib.For different inter-band rock positions,two ways of controlling rib by increasing supports stiffness and flexible grouting reinforcement are proposed.

Evaluating Privacy Leakage and Memorization Attacks on Large Language Models (LLMs) in Generative AI Applications

The recent interest in the deployment of Generative AI applications that use large language models (LLMs) has brought to the forefront significant privacy concerns, notably the leakage of Personally Identifiable Information (PII) and other confidential or protected information that may have been memorized during training, specifically during a fine-tuning or customization process. We describe different black-box attacks from potential adversaries and study their impact on the amount and type of information that may be recovered from commonly used and deployed LLMs. Our research investigates the relationship between PII leakage, memorization, and factors such as model size, architecture, and the nature of attacks employed. The study utilizes two broad categories of attacks: PII leakage-focused attacks (auto-completion and extraction attacks) and memorization-focused attacks (various membership inference attacks). The findings from these investigations are quantified using an array of evaluative metrics, providing a detailed understanding of LLM vulnerabilities and the effectiveness of different attacks.

Percutaneous antegrade management of large proximal ureteral stones using non-papillary puncture

Objective:To evaluate the feasibility and the safety of medial non-papillary percutaneous nephrolithotomy(npPCNL)for the management of large proximal ureteral stones.Methods:We evaluated prospectively collected data of 37 patients with large proximal ureteral stones more than 1.5 cm in diameter treated by prone npPCNL.Depending on stone size,in-toto stone removal or lithotripsy using the Lithoclast®Trilogy(EMS Medical,Nyon,Switzerland)was performed.Perioperative parameters including operative time(from start of puncture to the skin suturing),stone extraction time(from the first insertion of the nephroscope to the extraction of all stone fragments),and the stone-free rate were evaluated.Results:Twenty-one males and 16 females underwent npPCNL for the management of large upper ureteral calculi.The median age and stone size of treated patients were 58(interquartile range[IQR]:51-69)years and 19.3(IQR:18.0-22.0)mm,respectively.The median operative time and stone extraction time were 25(IQR:21-29)min and 8(IQR:7-10)min,respectively.One case(2.7%)of postoperative bleeding and two cases(5.4%)of prolonged fever were managed conservatively.The stone-free rate at a 1-month follow-up was 94.6%.Conclusion:The npPCNL provides a straight route to the ureteropelvic junction and proximal ureter.Approaching from a dilated portion of the ureter under low irrigation pressure with larger diameter instruments results in effective and safe stone extraction within a few minutes.

Hydromassage of macular hole edges for large and persistent full-thickness macular holes

●AIM:To introduce the macular hole(MH)hydromassage technique as a potentially beneficial approach for the treatment of large or persistent MH.●METHODS:This retrospective observational case series comprised 16 consecutive patients(17 eyes)diagnosed with MH.Inclusion criteria involved a hole aperture diameter larger than 600μm or the presence of an unclosed MH larger than 600μm following the previous vitrectomy.Standard MH repair procedures were administered in all cases,involving the manipulation and aspiration of the hole margin through the application of water flow with a soft-tip flute needle.A comprehensive assessment was conducted for each case before and after surgery,and optical coherence tomography(OCT)images were captured at every follow-up point.●RESULTS:The mean preoperative aperture diameter was 747±156μm(range 611-1180μm),with a mean base diameter of 1390±435μm(range 578-2220μm).Following surgery,all cases achieved complete anatomical closure of MH,with 13 cases(76.5%)exhibiting type 1 closure and 4 cases(23.5%)demonstrating type 2 closure.No significant differences were observed in the preoperative OCT variables between the two closure types.Eyes with type 1 closure showed a significantly improved visual acuity(0.70±0.10,range 0.50-0.80)compared to those with type 2 closure(0.90±0.12,range 0.80-1.00,P=0.014).●CONCLUSION:The MH hydromassage technique demonstrates promising results,achieving acceptable closure rates in cases of large or persistent MH.This technique may serve as an effective adjunctive maneuver during challenging MH surgery.

The environmental analysis and site selection of mussel and large yellow croaker aquaculture areas based on high resolution remote sensing

Mussel aquaculture and large yellow croaker aquaculture areas and their environmental characteristics in Zhoushan were analyzed using satellite data and in-situ surveys.A new two-step remote sensing method was proposed and applied to determine the basic environmental characteristics of the best mussel and large yellow croaker aquaculture areas.This methodology includes the first step of extraction of the location distribution and the second step of the extraction of internal environmental factors.The fishery ranching index(FRI1,FRI2)was established to extract the mussel and the large yellow croaker aquaculture area in Zhoushan,using Gaofen-1(GF-1)and Gaofen-6(GF-6)satellite data with a special resolution of 2 m.In the second step,the environmental factors such as sea surface temperature(SST),chlorophyll a(Chl-a)concentration,current and tide,suspended sediment concentration(SSC)in mussel aquaculture area and large yellow croaker aquaculture area were extracted and analyzed in detail.The results show the following three points.(1)For the extraction of the mussel aquaculture area,FRI1 and FRI2 are complementary,and the combination of FRI1 and FRI2 is suitable to extract the mussel aquaculture area.As for the large yellow croaker aquaculture area extraction,FRI2 is suitable.(2)Mussel aquaculture and the large yellow croaker aquaculture area in Zhoushan are mainly located on the side near the islands that are away from the eastern open waters.The water environment factor template suitable for mussel and large yellow croaker aquaculture was determined.(3)This two-step remote sensing method can be used for the preliminary screening of potential site selection for the mussels and large yellow croaker aquaculture area in the future.the fishery ranching index(FRI1,FRI2)in this paper can be applied to extract the mussel and large yellow croaker aquaculture areas in coastal waters around the world.

Evaluating the Impacts of Human Activities on Diversity, Abundance, and Distribution of Large Mammals in Nimule National Park, South Sudan

Globally, human activities have a significant impact on the diversity, abundance, and distribution of large mammals in Protected Areas (PAs). These disturbances increase human pressure on biodiversity and species habitats, highlighting the need for conservation. This study aimed to assess the abundance and distribution of large mammals in different habitat types within Nimule National Park (NNP) and understand the impacts of human activities on them. Data on the abundance and distribution of large mammals and their respective habitat types were collected through line transect surveys. Human activity signs were observed and recorded along the transect lines. To estimate the impacts of human activities on the diversity, abundance, and distribution of large mammal species, as well as to identify any significant differences between them and their habitat types, the study utilized the Kruskal Wallis test, Polynomial multiple regressions, and diversity indices. The findings from the Shannon-Weiner and Simpson indices indicated that large mammal species were more diverse inside the park (H’ = 1.136;D = 0.570) compared to the buffer zone (H’ = 0.413;D = 0.171), with 85% (443 out of 510 samples) recorded within Nimule National Park. The species abundance showed a semi-balanced status (0.58). The diversity results among different habitat types revealed that large mammals were more diverse and highly distributed in both open woodlands (244) and dense woodlands (192), while riverine vegetation had the lowest diversity (8). Statistical tests demonstrated a highly significant difference at a 99% confidence interval (p-value = 0.01) between habitat types and identified species of large mammals. Additionally, the results highlighted the high abundance of Uganda kob (274), baboons (141), and warthog (57) across most habitat types, accounting for at least 75% of their distribution. The most prevalent human activities observed were cattle footprints (27%) and cattle dung (14%). Human footprints and tree cutting combined accounted for 9%, indicating the practice of livestock grazing, poaching, encroachment, and fuelwood collection by local communities. However, these activities did not appear to significantly impact the diversity, abundance, and distribution of large mammals in Nimule National Park. Therefore, it is crucial to foster shared responsibilities and engage relevant stakeholders in the management and conservation of large wildlife species. Regular community awareness programs should be implemented to cultivate a sense of ownership. Moreover, it is recommended that a comprehensive survey be conducted on the population status of all mammal species in Nimule National Park, including its surrounding Buffer Zone. Monitoring the impact of human activities on their behavior and habitats using satellite images should also be carried out at least every five to ten years.

Relativistic Heavy Ion Collider and the Large Hadron Collider for Heavy Ion Fusion

Heavy Ion Fusion makes use of the Relativistic Heavy Ion Collider at Brookhaven National Lab and the Large Hadron Collider in Geneva, Switzerland for Inertial Confinement Fusion. Two Storage Rings, which may or may not initially be needed, added to each of the Colliders increases the intensity of the Heavy Ion Beams making it comparable to the Total Energy delivered to the DT target by the National Ignition Facility at the Lawrence Livermore Lab. The basic Physics involved gives Heavy Ion Fusion an advantage over Laser Fusion because heavy ions have greater penetration power than photons. The Relativistic Heavy Ion Collider can be used as a Prototype Heavy Ion Fusion Reactor for the Large Hadron Collider.

Primary anaplastic lymphoma kinase-positive large B-cell lymphoma of the left bulbar conjunctiva: A case report

BACKGROUND Anaplastic lymphoma kinase(ALK)-positive large B-cell lymphoma(LBCL)is an aggressive and rare variant of diffuse LBCL.Herein,we report an uncommon case of stage IE extranodal ALK-positive LBCL initially originating in the bulbar con-junctiva.CASE SUMMARY A 63-year-old woman presented with a mass in the left bulbar conjunctiva that had persisted for six months,accompanied by swelling and pain that had per-sisted for 3 d.Eye examination revealed an 8 mm slightly elevated pink mass in the lower conjunctival sac of the left eye.Microscopically,the tumor was com-posed of large immunoblastic and plasmablastic large lymphoid cells with scattered anaplastic or multinucleated large cells.Immunophenotypically,the neoplastic cells were positive for ALK,CD10,CD138,Kappa,MUM1,BOB.1,OCT-2,CD4,CD45,EMA,CD79a,CD38,and AE1/AE3,and negative for CD20,PAX5,Lambda,BCL6,CD30 and all other T-cell antigens.The results of gene rearrangement tests showed monoclonal IGH/IGK/IGL and TCRD rearran-gements.Fluorescence in situ hybridization studies did not reveal any BCL2,BCL6 or MYC rearrangements.Furthermore,Epstein-Barr virus was not detected by in situ hybridization in the lesions.Based on the histopathological and imaging examinations,the neoplasm was classified as stage IE ALK-positive LBCL.No further treatments were administered.At the 6,15,and 21 mo postoperative follow-up visits,the patient was in good condition,without obvious discomfort.This case represents the first example of primary extranodal ALK-positive LBCL presenting as a bulbar conjunctival mass,which is extremely rare and shares morphological and immunohistochemical features with a variety of other neo-plasms that can result in misdiagnosis.CONCLUSION Awareness of the condition presented in this case report is necessary for early and accurate diagnosis and appropriate treatment.

Potential use of large language models for mitigating students’problematic social media use:ChatGPT as an example

The problematic use of social media has numerous negative impacts on individuals'daily lives,interpersonal relationships,physical and mental health,and more.Currently,there are few methods and tools to alleviate problematic social media,and their potential is yet to be fully realized.Emerging large language models(LLMs)are becoming increasingly popular for providing information and assistance to people and are being applied in many aspects of life.In mitigating problematic social media use,LLMs such as ChatGPT can play a positive role by serving as conversational partners and outlets for users,providing personalized information and resources,monitoring and intervening in problematic social media use,and more.In this process,we should recognize both the enormous potential and endless possibilities of LLMs such as ChatGPT,leveraging their advantages to better address problematic social media use,while also acknowledging the limitations and potential pitfalls of ChatGPT technology,such as errors,limitations in issue resolution,privacy and security concerns,and potential overreliance.When we leverage the advantages of LLMs to address issues in social media usage,we must adopt a cautious and ethical approach,being vigilant of the potential adverse effects that LLMs may have in addressing problematic social media use to better harness technology to serve individuals and society.