With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

Although video-assisted thoracoscopic surgery (VATS) offers clear advantages, including minimal trauma and rapid recovery, stable intraoperative visualization still depends heavily on the camera assistant. Traditional manual endoscope holding is therefore susceptible to several limitations, including image instability, assistant fatigue, and poor coordination with the primary surgeon. Operating in complex and confined anatomical spaces with a rigid thoracoscope further increases the demands on hand-eye coordination. Thoracoscopic camera-holding technology has progressively evolved from passive support systems to active camera holders and robot-assisted thoracic surgery (RATS) platforms, and is now advancing toward artificial intelligence-driven tracking and intelligent control. Based on this, a series of devices, including multifunctional intelligent assistant arms and active camera-holding arms for thoracic surgery, have been developed and have attracted increasing attention. This article reviews the development of intelligent camera-holding assistant arms and discusses related advances and future directions in the field.

ObjectiveTo investigate the value of liver stiffness measurement （LSM） and spleen stiffness measurement （SSM） measured by two-dimensional shear wave elastography （2D-SWE） in the diagnosis of severe portal hypertension （SPH） and high-risk varices （HRV）， and to provide a basis for noninvasive assessment of portal hypertension. MethodsA prospective study was conducted among 78 patients with cirrhotic portal hypertension who were treated in Liver Research Center of Beijing Friendship Hospital， Capital Medical University， from December 2019 to April 2023. According to hepatic venous pressure gradient （HVPG）， the patients were divided into 6 mmHg≤HVPG<12 mmHg group， 12 mmHg≤HVPG<20 mmHg group， and HVPG ≥20 mmHg group. All patients underwent gastroscopy and 2D-SWE within 1 week after HVPG measurement， and SWE-LSM and SWE-SSM measured by 2D-SWE were recorded. A one-way analysis of variance or the Kruskal-Wallis H test was used for comparison of continuous data between multiple groups， and the chi-square test or the Fisher’s exact test was used for comparison of categorical data between groups. With HVPG and gastroscopy findings as the gold standard， the receiver operating characteristic （ROC） curve was plotted and the area under the ROC curve （AUC） was calculated to evaluate diagnostic performance， while the DeLong test was used for comparison of AUC. The Pearson or Spearman correlation analysis was used to investigate the correlation between variables， and the linear regression analysis and the Logistic regression analysis were used to investigate the influencing factors for HVPG and HRV. ResultsThe mean HVPG was 18.1±6.4 mmHg for the patients enrolled in this study， and HRV was observed in 62 patients （79.5%）. Both SWE-LSM and SWE-SSM were significantly positively correlated with HVPG （r=0.413 and 0.633， both P<0.001）， with an AUC of 0.812 and 0.902， respectively， in the diagnosis of HVPG≥12 mmHg and an AUC of 0.804 and 0.789， respectively， in the diagnosis of HVPG≥20 mmHg （all P>0.05）. The multivariate linear regression analysis showed that SWE-SSM was an independent influencing factor for HVPG （β=0.17， P<0.001）. In the diagnosis of HRV， only SWE-SSM showed a significant positive correlation with HRV （r=0.432， P<0.001）， with a better diagnostic performance than SWE-LSM in terms of AUC （0.808 vs 0.642， Z=2.775， P=0.006）. The multivariate Logistic regression analysis showed that platelet count was an independent influencing factor for HRV （odds ratio=0.97， P=0.014）. ConclusionSWE-SSM is closely correlated with both HVPG and HRV， showing a good performance in the diagnosis of SPH and HRV， and therefore， it is expected to become an effective noninvasive tool for assessing portal hypertension.

ObjectiveTo construct a prediction model for high responsiveness to short-term aerobic training in patients with Parkinson's disease (PD) based on dual-task gait assessment, and to provide evidence for identifying individuals who are most likely to benefit from such interventions. MethodsA total of 42 patients with PD who visited the outpatient clinic of Tianjin Huanhu Hospital between August 29, 2023 and December 19, 2024 were enrolled. All participants completed a 4-week home-based aerobic cycling training program and underwent dual-task gait assessments pre- and post-training. Patients were classified into high-response group (n = 12) and low-response group (n = 30) according to whether the improvement in gait speed reached the minimal clinically important difference of 0.1 m/s. The clinical validity of this grouping was verified by comparing differences in cardiopulmonary exercise testing parameters and dual-task gait indicators between the two groups pre- and post-training. Based on baseline characteristics, Firth's penalized maximum likelihood logistic regression was applied to construct a predictive model for high responsiveness, and the discriminative performance of the model was assessed preliminarily. ResultsThe high-response group showed significantly greater improvement in gait speed, step length, cadence and the anaerobic threshold to maximal oxygen uptake ratio after training compared with the low-response group (P < 0.05), confirming the clinical validity of the grouping. The baseline anaerobic threshold to maximal oxygen uptake ratio (OR = 3.348), body mass index (OR = 2.229) and age (OR = 0.428) demonstrated certain discriminative ability in the present sample. The area under the receiver operating characteristic curve was 0.831, with an overall prediction accuracy of 81.0%, specificity of 83.3% and sensitivity of 75.0%. Robustness of the model was confirmed via internal validation using the Bootstrap method, which suggested that the results were informative, but further validation was still required. ConclusionThe anaerobic threshold/maximal oxygen uptake ratio, body mass index and age may predict the response to short-term aerobic training in patients with PD.

ObjectiveHepatocellular carcinoma (HCC) represents 90% of all primary liver cancers. The main risk factors associated with HCC include viral hepatitis (B and/or C), alcohol abuse, and metabolic dysfunction-associated steatotic liver disease (MASLD), which progressively advance to liver fibrosis, cirrhosis, and ultimately evolve into HCC. Surgical resection represents the most effective treatment for HCC, while recent advances in immunotherapy, including immune checkpoint inhibitors and adoptive cell therapies, have provided improved treatment prospects for patients with unresectable HCC. However, the complex metabolic heterogeneity of HCC limits the therapeutic efficacy. Metabolic intermediates acyl-CoA not only provide energy and substrates for numerous biochemical reactions but also serve as donors for protein lysine acylation, a major class of post-translational modification (PTM). Therefore, a deeper understanding of the molecular mechanisms underlying protein lysine acylation and hepatocarcinogenesis is urgently needed. MethodsThe levels of protein lysine acylation and silence information regulator 5 (SIRT5) expression levels in clinical HCC samples were analyzed by Western blot. Quantitative malonylome and succinylome of HCC samples were analyzed by antibody-based affinity enrichment coupled with tandem mass spectrometry. The proliferation of HCC cells was analyzed with Cell Counting Kit-8 (CCK-8) assays, the apoptosis was quantified by Annexin V-FITC/propidium iodide (PI) staining coupled with flow cytometry, and the ability of cells to migrate was assayed by Transwell assays. The enzymatic activity of glutathione S-transferase Mu 1 (GSTM1) was quantified. Transgenic mice with hepatic overexpression of SIRT5 were constructed using CRISPR-Cas9, and primary hepatocarcinogenesis was induced by administration of diethylnitrosamine. ResultsWestern blot analysis indicated that the expression level of SIRT5 was elevated in clinical samples from HCC patients, and the levels of lysine malonylation, glutarylation, and succinylation were significantly reduced in HCC tissues. Knockout of SIRT5 in MHCC-97H and MHCC-97L hepatoma cells suppressed cell proliferation, and increased the percentage of apoptotic cells significantly. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the differentially malonylome and succinylome of HCC samples revealed significant enrichment in two major classes of biological processes: core energy metabolism (e.g., glycolysis/gluconeogenesis, tricarboxylic acid metabolic process, fatty acid beta oxidation) and detoxification and oxidative stress response (e.g., response to toxic substance, chemical carcinogenesis, reactive oxygen species (ROS)). SIRT5 removes malonylation from lysine residues in GSTM1 and restores its detoxification activity, which is crucial for the survival of hepatocytes under stressed conditions. More importantly, in vivo experiment indicated that hepatic-specific overexpression of SIRT5 in mice accelerated diethylnitrosamine-induced liver fibrosis and hepatocarcinogenesis, indicating the critical role of SIRT5 in HCC progression. ConclusionThis study highlights the previously unrecognized SIRT5-GSTM1 axis as a key regulator in hepatocarcinogenesis, and suggests a potential target for the treatment of patients with HCC.

ObjectiveThe Golgi apparatus serves as a central hub in the eukaryotic secretory pathway, responsible for the processing, sorting, and trafficking of proteins and lipids. In mammalian cells, the Golgi typically forms a perinuclear ribbon-like structure composed of laterally connected cisternae stacks.The maintenance of Golgi ribbon structure depends on the balance of membrane flux across multiple intracellular trafficking pathways, yet the specific contributions of distinct trafficking branches to Golgi macroscopic morphology remain elusive. In mammalian cells, the Golgi ribbon is typically organized as a perinuclear, laterally connected structure composed of stacked cisternae, and its integrity is highly dynamic and sensitive to perturbations in membrane trafficking. This study aims to elucidate the role of coat protein complex I (COPI)-mediated retrograde transport in maintaining the Golgi ribbon and to dissect the functional relationship between the transmembrane cargo receptors LEPROT/LEPROTL1 (LEPROTs) and the COPI adaptor GOLPH3. MethodsUsing siRNA interference and gene-deficient cell lines, we selectively perturbed COPI- or adaptor protein complex 1 (AP-1)-mediated trafficking pathways in HeLa cells. To quantitatively evaluate Golgi morphology, we employed a “Golgi Angle”-based measurement to assess its circumferential distribution around the nucleus. The spatial distribution of the Golgi ribbon was quantitatively analyzed using confocal microscopy, while Golgi ultrastructure and vesicle density were examined via transmission electron microscopy. Additionally, the subcellular distribution of COPI components was assessed by immunofluorescence co-localization. ResultsSelective inhibition of COPI retrograde transport significantly induced the circumferential extension of the Golgi ribbon around the nucleus, whereas blocking AP-1-mediated anterograde transport resulted in Golgi compaction, indicating opposing roles. These results suggest that different trafficking branches downstream of ARF1 exert distinct and even antagonistic effects on Golgi morphology. LEPROTs-deficient cells exhibited a Golgi extension phenotype highly consistent with COPI impairment. Furthermore, knockdown of GOLPH3 in a LEPROTs double-knockout background produced a significant additive effect on Golgi extension, suggesting that LEPROTs and GOLPH3 play non-redundant roles in regulating COPI-related trafficking processes. Mechanistically, loss of either LEPROTs or GOLPH3 led to the aberrant accumulation of COPI components at endoplasmic reticulum exit sites, accompanied by a reduction in COPI-like vesicles around the Golgi. This redistribution indicates a defect in COPI recycling between the ER-Golgi interface and the Golgi apparatus. Ultrastructural analysis revealed that Golgi cisternae in defective cells became shorter and thicker while maintaining a stable number of stacks. In parallel, the density of Golgi-associated vesicles was markedly decreased, further supporting an impairment in COPI vesicle formation or budding processes. ConclusionThis study demonstrates that active COPI retrograde transport is a critical factor in restricting the over-connection of the Golgi ribbon and maintaining its compactness. Rather than causing fragmentation, partial disruption of COPI function leads to a distinct morphological outcome characterized by Golgi ribbon extension at the light microscopy level and cisternal remodeling at the ultrastructural level. LEPROTs and GOLPH3 cooperatively promote the recycling and vesiculation of COPI components, thereby imposing a structural constraint on the Golgi periphery. Our findings support a model in which multiple adaptor proteins act in parallel to sustain efficient COPI cycling, thereby maintaining Golgi structural homeostasis. These findings provide new cell biological evidence for the membrane trafficking basis of Golgi morphological homeostasis.

Objective To explore the feasibility and image quality of respiratory-gated total-body ¹⁸F-FDG PET/CT imaging with a 4-minute acquisition in patients with malignant tumors. Methods Sixty-two patients with pathologically confirmed malignant tumors (118 lesions measured) who underwent total-body ¹⁸F-FDG PET/CT examination were consecutively enrolled at the Department of Nuclear Medicine, Zhongshan Hospital, Fudan University, from September 23, 2021 to November 23, 2021, and their clinical and imaging data were retrospectively collected. PET data was acquired over 12 minutes with simultaneous respiratory waveform recorded. The data were reconstructed into four image sets: gated-12 group and gated-4 group (using all counts and the first 4-minute counts, respectively) and ungated-12 group and ungated-6 group (using all counts and the first 6-minute counts, respectively) reconstructed with respiratory gating that retained counts corresponding to the half respiratory window near end-expiration. Image quality assessment and quantitative analysis of lesions were performed and compared among the four image sets, and subgroup analyses were performed according to lesion location, size, and metabolic activity. Results The effective counts of 4 sets of PET images were highest in ungated-12 group, followed by ungated-6 group and gated-12 group, and lowest in gated-4 group (P＜0.001). Regardless of the metabolic level and size of the lesions, compared with the ungated-12 group and the ungated-6 group, the lesions in the gated-12 group showed higher maximum, average, and peak standardized uptake values (SUV_max, SUV_mean, and SUV_peak), tumor liver uptake ratio, tumor blood pool uptake ratio, and smaller metabolic volume (P＜0.05); There was no statistically significant difference in the above indicators between the gate-12 group and the gate-4 group. The background noise of gate-4 group images is slightly higher than that of gate-12 group images (Liver SUV_SD: [0.17＋0.05] vs [0.14＋0.04]); Blood pool SUV_SD: (0.08 ± 0.03) vs (0.06 ± 0.03). There was a statistically significant difference in subjective scores of PET image quality among the four groups (P＜0.001). The subjective scores of image quality in the gated-12 group (4.79 ± 0.41) were not significantly different from those in the non gated-12 group (4.97 ± 0.17) and non gated-6 group (4.79 ± 0.45), but were higher than those in the gated-4 group ([4.17 ± 0.45], P＜0.001)， And the scores have good consistency (Kappa＞0.75). Conclusion In total-body PET/CT imaging for malignant tumors, 4-minute respiratory-gated acquisition can achieve comparable quantitative performance to longer respiratory gating imaging while significantly shortening acquisition time. This approach demonstrates promising potential for clinical application.

ObjectiveThe essence of syndrome manifestation recognition in traditional Chinese medicine (TCM) is to infer the body’s latent pathogenesis state from clinical observational information, rather than to perform simple label matching. However, previous studies have largely modeled this task as syndrome pattern classification within a fixed label space, which does not adequately reflect the cognition process of TCM syndrome differentiation centered on pathogenesis reasoning, and is also insufficient to capture the openness, semantic variability, and cross-disease reusability of syndrome manifestation expression. This study aimed to investigate whether introducing pathogenesis reasoning chain-of-thought (PR-CoT) supervision into large language models (LLMs) could improve the quality and cognitive consistency of syndrome manifestation recognition and support cross-disease transfer. MethodsSyndrome manifestation recognition was formulated as a conditional generation task under the framework of clinical observational information (X)→pathogenesis structure (Z)→syndrome pattern output (Y), where Z serves as an explicit intermediate structural variable linking the clinical evidence and syndrome judgment. Within this framework, a PR-CoT-supervised dataset for syndrome manifestation recognition was constructed based on medical case records of spleen-stomach disorders. After preprocessing, information extraction, manual proofreading, and data cleaning, the dataset comprised 4 800 training cases, 400 development cases, and 400 test cases. Each sample was annotated with a structured PR-CoT consisting of three progressive levels: clinical information summarization, comprehensive pathogenesis analysis, and syndrome pattern output. Supervised fine-tuning was conducted on open-source LLMs, with an end-to-end model serving as the baseline. Qwen3-32B was used as the primary experimental model, and Qwen3-14B as the scale comparison model. A progressive multidimensional evaluation framework was further established, comprising a structural parsing level, a semantic similarity level, and an expert blind review level. At the structural parsing level, syndrome pattern expressions were decomposed into structural elements and evaluated using Precision, Recall, F1 score, and Jaccard similarity. At the semantic similarity level, independent LLMs scored the theoretical proximity between predicted and reference syndrome patterns. At the expert blind review level, three TCM experts independently evaluated model outputs on two dimensions: syndrome differentiation consistency and terminology standardization of syndrome patterns. In addition, zero-shot cross-disease transfer evaluation was conducted on gynecological and heart-system disorder test sets. ResultsAt the structural parsing level, PR-CoT supervision did not lead to a stable improvement in the element-wise overlap of syndrome pattern structural components. Compared with the corresponding baselines, neither Qwen3-32B nor Qwen3-14B showed consistent advantages in structural matching metrics after the introduction of PR-CoT supervision. In contrast, at the semantic similarity level, PR-CoT supervision produced stable positive gains across different model scales and evaluation systems. The average semantic score of Qwen3-32B increased from 6.425 8 in the baseline model to 6.585 0 after PR-CoT supervision, and that of Qwen3-14B increased from 5.870 0 to 5.964 2. At the expert blind review level, the overall score of Qwen3-32B (PR-CoT) was 7.026 0±0.107 7, higher than 6.416 3±0.288 9 for its baseline. In zero-shot cross-disease testing, the PR-CoT model still showed advantages in semantic evaluation and expert evaluation on both gynecological and heart-system disorder test sets, indicating a certain degree of transferability. ConclusionThe benefits of PR-CoT supervision are mainly reflected in TCM semantic consistency and clinical plausibility, rather than in improved hard matching of structural elements. These findings support understanding syndrome manifestation recognition as a process of generating and expressing latent pathogenesis structures, rather than as a classification task within a traditional fixed label space. By introducing pathogenesis reasoning as an explicit intermediate structure into the modeling process and combining it with a progressive multidimensional evaluation framework, this study provides a methodological pathway for intelligent TCM syndrome differentiation that integrates theoretical alignment, interpretability, and multi-level evaluation.

ObjectiveThis paper aims to systematically reveal the effect difference and mechanisms of Zishenwan against chronic prostatitis （CP） before and after salt-processing of Anemarrhenae rhizoma and Phellodendri chinensis cortex based on an integrated strategy of ultra-high performance liquid chromatography-quadrupole-orbitrap mass spectrometry （UPLC-Q-Orbitrap-MS/MS）， network pharmacology， and serum metabolomics. MethodsZishenwan samples before and after salt-processing of Anemarrhenae rhizoma and Phellodendri chinensis cortex were extracted by alcohol-water dual extraction. The chemical components of each sample were detected by UPLC-Q-Orbitrap-MS/MS， and differential components were screened by multivariate statistical analysis. Network pharmacology analysis was performed based on the identified chemical components of Zishenwan to construct a protein-protein interaction （PPI） network of "component， target， and pathway"， and the core components， targets， and pathways of Zishenwan against CP were screened. Forty-two male Sprague-Dawley （SD） rats were randomly divided into a blank group， a model group， a Qianliekang group （1.54 g·kg^-1）， low- and high-dose raw Zishenwan groups （1.8， 5.4 g·kg^-1）， and low- and high-dose salt-processed Zishenwan groups （1.8， 5.4 g·kg^-1）. The CP rat model was established by intraprostatic injection of carrageenan. After one week of recovery， the rats were administered the corresponding drugs for 21 days， while those in the blank group and model group received the same volume of normal saline. After the experiment， serum and tissue samples were collected to evaluate pharmacodynamic indicators including organ indices， histopathology， and inflammatory factors in serum. Subsequently， untargeted serum metabolomics technology was used to analyze metabolite changes and perform pathway enrichment analysis. The network pharmacology was used to construct a network of "differential metabolite， reaction， enzyme， and gene". ResultsA total of 76 components were identified in raw and salt-processed Zishenwan， and 34 differential components were screened by multivariate statistical analysis. Among them， the contents of 14 components， including berberine， berberrubine， and phellodendrine， increased after salt-processing， while the contents of 20 components， such as neomangiferin， decreased. The 28 active components and 185 potential targets were screened out by network pharmacology. The core components included berberine， phellodendrine， magnoflorine， and jatrorrhizine， and the core targets included signal transducer and activator of transcription 3 （STAT3）， protein kinase B1 （Akt1）， and transcription factor AP-1 （JUN）. These targets were significantly enriched in pro-inflammatory signaling pathways such as phosphatidylinositol 3-kinase/protein kinase B （PI3K/Akt） and mitogen-activated protein kinase （MAPK）. Compared with the model group， all Zishenwan administration groups showed decreased prostate index， reduced levels of interleukin （IL）-1β， IL-18， and B-cell lymphoma-2 （Bcl-2） in serum （P<0.05， P<0.01）， as well as varying degrees of alleviation in histopathological damage. At the same dose， compared with the raw Zishenwan groups， the salt-processed Zishenwan groups showed lower prostate index， pathological scores， and IL-1β， IL-18， and Bcl-2 levels in serum， but the differences were not statistically significant. Metabolomics reveals that 38 differential metabolites were reversed after salt-processed Zishenwan administration. Both raw and salt-processed Zishenwan regulated pathways such as β-alanine metabolism and tryptophan metabolism. In addition to the common regulated pathways， the salt-processed group specifically regulated pantothenate and coenzyme A biosynthesis， pyrimidine metabolism， and arginine and proline metabolism. The intersecting pathways between network pharmacology and metabolomics were tryptophan metabolism and arginine and proline metabolism， with overlapping targets including monoamine oxidase A （MAOA） and arginase 1 （ARG1）. ConclusionThe increased contents of components such as berberine and phellodendrine in salt-processed Zishenwan may enhance its therapeutic effect on CP by inhibiting the PI3K/Akt and MAPK signaling pathways， along with multi-target regulation of tryptophan， arginine， and pantothenate metabolism pathways to comprehensively regulate inflammatory and immune responses.

BACKGROUND:Exosomes derived from mesenchymal stem cells play pivotal roles in cell communication and epigenetic regulation due to their low immunogenicity and targeted delivery effects,and have been clinically applied in the treatment of various diseases.OBJECTIVE:To review the isolation,purification,identification methods,and application progress of mesenchymal stem cell-derived exosomes,and to facilitate the development of large-scale preparation techniques and clinical translation of mesenchymal stem cell-derived exosomes.METHODS:The Chinese search terms"exosome,mesenchymal stem cells,isolation,purification,characterization,clinical application"and the English search terms"exosome,extracellular vesicles,mesenchymal stem cells,isolation,characterization,application"were used to search the literature published before September 2024 in CNKI,PubMed,and Web of Science databases.Articles with poor relevance to the topic,outdated,or duplicated content were excluded,and finally,109 articles were included for review.RESULTS AND CONCLUSION:(1)This paper reviews recent methods for isolating and purifying exosomes,comparing the characteristics of ultracentrifugation,ultrafiltration,size-exclusion chromatography,polymer precipitation,immunoaffinity,microfluidic methods,and other novel approaches based on their underlying principles.(2)Methods for identifying exosomes can be categorized into physical and biochemical analyses,characterizing exosomes based on their shape,size,and characteristic proteins.(3)Mesenchymal stem cell-derived exosomes have broad applications in multiple fields such as medical aesthetics,wound repair,and cancer treatment,due to their immune-regulatory properties and ability to cross biological barriers.(4)The clinical translation of exosomes faces challenges due to their complex structure,lack of universal isolation techniques,and poor stability,making it difficult to achieve in a short period of time.