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.

Background/Aims: Liver transplantation (LT) following total hepatectomy is a life-saving treatment for hepatocellular carcinoma (HCC). The HCC recurrence after LT hinders the effectiveness of the procedure. The objective of this study is to develop a pre-operative risk stratification model based on a liquid biopsy. Methods: We conducted a comprehensive multi-omics study of 260 HCC patients from three centers, including clinical data, low-coverage whole-genome sequencing of cell-free DNA (cfDNA) from plasma, as well as whole-exome, single-nucleus RNA, and spatial transcriptomics from matched tumor and non-tumor tissues. Results: We identified cfDNA-derived copy number alteration (CNA) signatures associated with post-transplant recurrence. By integrating cfDNA-derived CNA profiles with single-cell transcriptomic data, we traced recurrence-associated cfDNA to a distinct subpopulation of malignant cells within the primary tumor. These cells were embedded in a pro-metastatic microenvironment of specialized endothelial subtypes and cancer-associated fibroblasts. Notably, most recurrence-associated lesions were detectable in cfDNA prior to liver transplantation (LT). Building on these insights, we developed the ZJU Criteria based on CNA fragments and tumor markers, a pre-LT risk prediction tool that integrates conventional clinical factors with cfDNA-derived CNA signatures, and validated it using internal and independent external cohorts. Conclusion Our findings suggest that post-transplant recurrence commonly originates from advanced subclones that emerge late during tumor evolution. The ZJU Criteria provides an accurate, non-invasive strategy that significantly improves pre-LT risk stratification and clinical decision-making for patients with HCC.

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.

ObjectiveCerebrospinal fluid (CSF) plays a crucial role in maintaining the homeostasis of the central nervous system (CNS). CSF rapidly exchanges with interstitial fluid (ISF) via the glymphatic system within the brain parenchyma. CSF-ISF circulation and its associated mechanisms are often referred to as the brain lymphatic system. This system is connected directly to meningeal lymphatic vessels (mLVs), jointly performing the function of clearing metabolic waste from the CNS. Emerging evidence indicates that this system is closely associated with the onset and progression of neurodegenerative diseases (NDs) such as Alzheimer’s disease (AD). Importantly, abnormal CSF circulation is not only a downstream consequence of AD pathology, but also a risk factor. In AD, the dynamics of CSF flow within the CNS are diminished, immune dysregulation occurs, and this may increase the risk of AD by exacerbating the burden of amyloid β-protein (Aβ). In the mouse model of AD, impaired CSF flow compromises this clearance function, leading to cognitive deficits. Clinically, acupuncture at cognition-related acupoints is commonly used for the prevention and treatment of AD. However, whether its therapeutic effects are mediated through the modulation of CSF dynamics remains unclear. This study aimed to evaluate the impact of acupuncture on CSF flow and investigate its acupoint specificity. MethodsMice were randomly assigned to experimental groups for the different electroacupuncture groups with the following acupoints: Baihui point (GV 20), Ear point, Neiguan point (PC 6), and Tianshu point (ST 25). Wild-type mice on a C57BL/6J background were used as controls. Fluorescent tracer was injected into the cisterna magna to label CSF flow. Fluorescence imaging was employed to assess the distribution of CSF within the brain before and after acupuncture stimulation. ResultsFollowing tracer injection into the cisterna magna, fluorescence signals rapidly reached the cerebellum and medulla—the regions closest to the injection site. Fluorescence intensity was higher in ventral brain regions compared to dorsal regions, likely due to greater vascular density in ventral areas facilitating CSF-ISF exchange. Electroacupuncture at the GV 20 produced the most pronounced enhancement of CSF across the whole brain, while stimulation at the ST 25 primarily augmented flow within subcortical regions. In contrast, electroacupuncture at the Ear point or the PC 6 had no observable effect on CSF in mice. ConclusionElectroacupuncture promotes CSF flow into the brain parenchyma in an acupoint-specific manner, with GV 20 exhibiting the most pronounced enhancement of CSF dynamics. These findings suggest that acupuncture-mediated facilitation of CSF flow may represent a potential therapeutic strategy for preventing or delaying age-related cognitive decline.

BACKGROUND:Nanocell vesicles possess functions such as re-epithelialization,antioxidation,anti-inflammation,and regulation of extracellular matrix remodeling.Meanwhile,apoptotic bodies have the immunomodulatory effects.Therefore,the combination of the two to form nanofusion vesicles can synergistically promote the healing of diabetic skin wounds.OBJECTIVE:To elucidate the impact of nanofusion vesicles on skin wound healing in a diabetic murine model.METHODS:(1)Material preparation and characterization:The primary bone marrow mesenchymal stem cells of C57BL/6J neonatal mice and the neutrophil apoptotic bodies of C57BL/6J mice were isolated and extracted.The nanofusion vesicles were prepared by micro-extrusion mechanism.(2)In vitro experiment:MTT assay was used to detect the proliferative effect of different concentrations of nanofusion vesicles on NIH-3T3 cells and human umbilical vein endothelial cells.Reactive oxygen species fluorescence probe was used to detect the antioxidant effect of nano-fusion vesicles on NIH-3T3 cells treated with hydrogen peroxide(H2O2).The inhibitory effect of nanofusion vesicles on RAW 264.7 macrophage inflammation induced by lipopolyside was detected by real-time quantitative RT-qPCR.(3)In vivo experiment:36 male C57BL/6J mice were employed to develop a murine model of diabetes mellitus.Following the successful induction of diabetes,two circular full-thickness wounds,each with a diameter of 6 mm,were created on either side of the diabetic mice's spine using a skin punch.The mice were divided into three groups by random number table method.The control group was injected with 0.1 mL of phosphate buffer solution.The nanovesicle group was injected with 0.1 mL nanovesicles(25 μg/mL).The nanofusion vesicle group was injected with 0.1 mL nanofusion(25 μg/mL)vesicles.After treatment for three consecutive days,the wound healing and histomorphological changes were observed.RESULTS AND CONCLUSION:(1)In vitro experiment:nanofusion vesicles,when administered at concentrations ranging from 0 to 100 μg/mL,exhibited no toxic effects and promoted the proliferation of NIH-3T3 and HUVEC cell lines.Notably,a concentration of 25 μg/mL nanofusion vesicle significantly enhanced the proliferation of NIH-3T3 cells.Furthermore,the survival rate of human umbilical vein endothelial cells was observed to increase in correlation with escalating concentrations of nanofusion vesicles.Nanofusion vesicles had a good antioxidant effect.In comparison to the H2O2 group,the fluorescence signal indicative of reactive oxygen species was progressively diminished in both the nanovesicle group and the nanofusion vesicle group.Furthermore,nanofusion vesicles possessed anti-inflammatory capabilities,effectively mitigating the inflammatory response in macrophages triggered by lipopolysaccharide stimulation.(2)In vivo experiment:Hematoxylin-eosin and Masson's trichrome staining revealed that in comparison to the control group,both the nanovesicle group and the nanofusion vesicle group exhibited a significant increase in granulation tissue formation and collagen fiber deposition within the wounds by day 6.Notably,the nanofusion vesicle group displayed the most pronounced effects.On day 12,the wound of nanofusion vesicle group was significantly reduced,and the healing rate was significantly faster than that of other groups(P＜0.01),and the effect of promoting wound healing was the most significant.Our findings demonstrated that nanofusion vesicles exhibited superior pro-cell proliferative,antioxidant,and anti-inflammatory properties,thereby exerting a beneficial effect on the promotion of skin wound healing in diabetic mouse models.

Atherosclerosis (AS), the primary pathological contributor to cardiovascular diseases (CVDs), has increasingly affected younger populations due to modern dietary habits and sedentary lifestyles. Current diagnostic modalities, including ultrasound, MRI, and CT, primarily identify advanced lesions and inadequately evaluate plaque vulnerability, thereby hindering early detection. Conventional treatments, which involve long-term medications associated with side effects such as hepatic injury and surgical interventions that carry risks of restenosis and hemorrhage, underscore the urgent need for non-invasive, cost-effective early diagnostic methods and targeted therapies. Gut microbiota metabolites are pivotal in AS pathogenesis, with trimethylamine N-oxide (TMAO) and short-chain fatty acids (SCFAs) serving as functionally opposing biomarkers. TMAO is produced when gut bacteria, specifically Firmicutes and Proteobacteria, metabolize dietary choline and carnitine into trimethylamine (TMA), which the liver subsequently converts to TMAO via flavin-containing monooxygenase 3 (FMO3); TMAO is then excreted in urine. Variability in TMAO levels is influenced by marine food consumption and FMO3 modulation, which can be affected by genetics, age, and diet. Mechanistically, TMAO exacerbates AS by disrupting cholesterol metabolism, inducing endothelial dysfunction through the elevation of reactive oxygen species (ROS) and pro-inflammatory cytokines such as IL-6, and reducing nitric oxide levels. Additionally, TMAO activates NF-κB and NLRP3 pathways while enhancing platelet reactivity. Clinically, elevated TMAO levels correlate with early AS and serve as predictors of mortality in patients with stable coronary artery disease (CAD) and acute coronary syndrome (ACS), as well as major adverse cardiovascular events (MACE) in stroke patients. Conversely, SCFAs—namely acetate, propionate, and butyrate—are produced by gut bacteria such as Akkermansia muciniphila and Faecalibacterium prausnitzii through the fermentation of dietary fiber. These metabolites exert anti-AS effects: acetate aids in maintaining metabolic homeostasis; propionate protects endothelial function and reduces plaque area; and butyrate fortifies intestinal barriers while suppressing inflammation. Furthermore, SCFAs cross-regulate bile acid metabolism, thereby influencing TMAO levels, and antagonize the pro-inflammatory and lipid-disrupting effects of TMAO. The use of TMAO and SCFAs as standalone biomarkers is constrained by limitations. TMAO lacks specificity, while SCFA levels fluctuate based on gut microbiota and dietary intake. Traditional AS risk assessment tools, which include clinical indicators, imaging techniques, and single biomarkers such as CRP, LDL-C, and ASCVD scores, overlook gut metabolism and demonstrate inadequate performance in younger populations. This review advocates for an “antagonistic-complementary” combined strategy: utilizing acetate and TMAO for early AS, propionate and TMAO for progressive AS, and butyrate and TMAO for advanced AS, addressing endothelial dysfunction, lipid deposition, and plaque stability/thrombosis risk, respectively. For clinical application, standardization of detection methods is crucial; liquid chromatography-mass spectrometry (LC-MS) is the gold standard, necessitating a unified sample pretreatment protocol, such as extraction with 1% formic acid in methanol. Additionally, dried blood spots (DBS) facilitate non-invasive testing, provided that dietary controls are implemented prior to detection, including a 12-hour fast and avoidance of high-choline and high-fiber foods. Existing challenges encompass the absence of standardized systems, limited large-scale validation, and ambiguous interactions with conditions such as hypertension. The authors’ team has previously established connections between gut metabolites and AS, including the reduction of TMAO as a preventive measure for AS, thereby reinforcing this proposed strategy. Future research should prioritize standardization, the development of machine learning-optimized models, validation of interventions, and the exploration of multi-omics-based “gut microbiota-metabolite-vascular” networks. In conclusion, the combined detection of TMAO and SCFAs offers a novel framework for AS risk assessment, facilitating early diagnosis and targeted interventions while enhancing the integration of gut metabolism into cardiovascular disease management.

Atherosclerosis (AS), the primary pathological contributor to cardiovascular diseases (CVDs), has increasingly affected younger populations due to modern dietary habits and sedentary lifestyles. Current diagnostic modalities, including ultrasound, MRI, and CT, primarily identify advanced lesions and inadequately evaluate plaque vulnerability, thereby hindering early detection. Conventional treatments, which involve long-term medications associated with side effects such as hepatic injury and surgical interventions that carry risks of restenosis and hemorrhage, underscore the urgent need for non-invasive, cost-effective early diagnostic methods and targeted therapies. Gut microbiota metabolites are pivotal in AS pathogenesis, with trimethylamine N-oxide (TMAO) and short-chain fatty acids (SCFAs) serving as functionally opposing biomarkers. TMAO is produced when gut bacteria, specifically Firmicutes and Proteobacteria, metabolize dietary choline and carnitine into trimethylamine (TMA), which the liver subsequently converts to TMAO via flavin-containing monooxygenase 3 (FMO3); TMAO is then excreted in urine. Variability in TMAO levels is influenced by marine food consumption and FMO3 modulation, which can be affected by genetics, age, and diet. Mechanistically, TMAO exacerbates AS by disrupting cholesterol metabolism, inducing endothelial dysfunction through the elevation of reactive oxygen species (ROS) and pro-inflammatory cytokines such as IL-6, and reducing nitric oxide levels. Additionally, TMAO activates NF-κB and NLRP3 pathways while enhancing platelet reactivity. Clinically, elevated TMAO levels correlate with early AS and serve as predictors of mortality in patients with stable coronary artery disease (CAD) and acute coronary syndrome (ACS), as well as major adverse cardiovascular events (MACE) in stroke patients. Conversely, SCFAs—namely acetate, propionate, and butyrate—are produced by gut bacteria such as Akkermansia muciniphila and Faecalibacterium prausnitzii through the fermentation of dietary fiber. These metabolites exert anti-AS effects: acetate aids in maintaining metabolic homeostasis; propionate protects endothelial function and reduces plaque area; and butyrate fortifies intestinal barriers while suppressing inflammation. Furthermore, SCFAs cross-regulate bile acid metabolism, thereby influencing TMAO levels, and antagonize the pro-inflammatory and lipid-disrupting effects of TMAO. The use of TMAO and SCFAs as standalone biomarkers is constrained by limitations. TMAO lacks specificity, while SCFA levels fluctuate based on gut microbiota and dietary intake. Traditional AS risk assessment tools, which include clinical indicators, imaging techniques, and single biomarkers such as CRP, LDL-C, and ASCVD scores, overlook gut metabolism and demonstrate inadequate performance in younger populations. This review advocates for an “antagonistic-complementary” combined strategy: utilizing acetate and TMAO for early AS, propionate and TMAO for progressive AS, and butyrate and TMAO for advanced AS, addressing endothelial dysfunction, lipid deposition, and plaque stability/thrombosis risk, respectively. For clinical application, standardization of detection methods is crucial; liquid chromatography-mass spectrometry (LC-MS) is the gold standard, necessitating a unified sample pretreatment protocol, such as extraction with 1% formic acid in methanol. Additionally, dried blood spots (DBS) facilitate non-invasive testing, provided that dietary controls are implemented prior to detection, including a 12-hour fast and avoidance of high-choline and high-fiber foods. Existing challenges encompass the absence of standardized systems, limited large-scale validation, and ambiguous interactions with conditions such as hypertension. The authors’ team has previously established connections between gut metabolites and AS, including the reduction of TMAO as a preventive measure for AS, thereby reinforcing this proposed strategy. Future research should prioritize standardization, the development of machine learning-optimized models, validation of interventions, and the exploration of multi-omics-based “gut microbiota-metabolite-vascular” networks. In conclusion, the combined detection of TMAO and SCFAs offers a novel framework for AS risk assessment, facilitating early diagnosis and targeted interventions while enhancing the integration of gut metabolism into cardiovascular disease management.

OBJECTIVE To investigate the effects of baicalin （BC） on insulin resistance in rats with gestational diabetes mellitus （GDM） and its underlying mechanism based on the adenosine monophosphate-activated protein kinase （AMPK）/suppressor of variegation 3-9 homolog 1 （SUV39H1）/histone H3 lysine 9 trimethylation （H3K9me3） axis. METHODS A GDM rat model was established by a combination of a high-fat diet and streptozotocin injection. The successfully modeled rats were divided into the GDM group， BC low-dose group， BC high-dose group， and high-dose of BC+AMPK inhibitor （Compound C） group， with 10 rats in each group. Another 10 pregnant rats fed a normal diet served as the control group. Rats in each group were given corresponding drugs/normal saline intragastrically and/or intraperitoneally， once daily for 2 consecutive weeks. After the last administration， the levels of fasting blood glucose （FBG）， pancreatic function indexes [fasting insulin （FINS）， homeostasis model assessment of insulin resistance （HOMA-IR）， insulin sensitivity index （ISI）]， blood lipid indexes （total cholesterol， triglyceride， low-density lipoprotein cholesterol）， liver function indexes （alanine transferase， aspartate transferase， alkaline phosphatase）， inflammatory indicators （C-reactive protein， interleukin-1β， interleukin-6）， metabolic regulatory protein [complement-C1q/tumor necrosis factor-related protein 3 （CTRP3）]， insulin sensitivity related factors [glucose transporter 4 （GLUT4）， adiponectin]， and oxidative stress indicators [superoxide dismutase （SOD）， catalase （CAT）， malondialdehyde （MDA）] were measured. Pathological changes in liver tissue were observed， and the expressions of proteins related to the AMPK/SUV39H1/H3K9me3 axis in liver tissue were detected. RESULTS Compared with the GDM group， rats in the BC low- and high-dose groups showed varying degrees of improvement in pathological changes such as disordered cell arrangement， vacuolar degeneration， lipid deposition， and inflammatory cell infiltration in liver tissue. Their FBG and FINS levels， HOMA-IR， the levels of blood lipid indexes， liver function indexes， inflammatory indicators and MDA， and the expressions of SUV39H1 and H3K9me3 were significantly decreased or down-regulated， while metabolic regulatory protein， insulin sensitivity-related factors and AMPK protein phosphorylation levels were significantly increased （ P ＜0.05）. The improvement was more significant in the BC high-dose group （ P ＜0.05）. Compound C could significantly reverse the ameliorative effects of high-dose BC on the above quantitative indicators （ P ＜0.05）. CONCLUSIONS BC can significantly reduce oxidative stress and inflammatory responses， increase serum levels of CTRP3， GLUT4 and adiponectin， thereby improving insulin resistance in GDM rats. These effects may be related to the activation of AMPK and inhibition of SUV39H1-mediated H3K9me3 modification.

Abnormal activation of the Janus kinase/signal transducer and activator of transcription （JAK/STAT） signaling pathway is involved in the pathogenesis of diffuse large B-cell lymphoma （DLBCL）. In recent years， inhibitors targeting JAK2 and STAT3 have emerged as promising therapeutic candidates in DLBCL. This review summarizes the efficacy and safety profiles of JAK2 inhibitors （e.g.， ruxolitinib） and STAT3 inhibitors （direct small-molecule inhibitors， the antisense oligonucleotide， and proteolysis targeting chimeras， etc.） in preclinical models and clinical trials. Accumulating evidence indicates that JAK2 and STAT3 inhibitors exhibit antitumor activity and are generally well tolerated in a subset of DLBCL patients. Meanwhile， the development of novel drug delivery systems has significantly enhanced the stability， bioavailability， and targeting ability of the compounds. Furthermore， JAK2 and STAT3 inhibitors may exhibit synergistic effects when combined with other therapy strategies （such as combinations with B-cell receptor signaling pathway inhibitors， immunomodulators， or other targeted drugs）. However， current clinical applications are still in their early stages. Future research should concentrate on precision treatment strategies based on the genetic subtyping of DLBCL， and further refine the delivery systems for inhibitors as well as combination drug regimens to improve clinical outcomes.

Objective: To investigate the prevalence of depressive symptoms and their associated factors among students in Zhejiang Province, so as to provide evidence for targeted prevention strategies. Methods: A stratified cluster random sampling method was used to select 23 829 college students and primary and secondary school students aged 11-22 years in Zhejiang Province from December 2019 to February 2020. Depressive symptoms were assessed using the Center for Epidemiologic Studies Depression Scale (CES-D). Three machine learning algorithms, including Logistic regression, random forest, and eXtreme Gradient Boosting (XGBoost), were applied to construct predictive models, and key associated factors were identified by comparing model performance. Results: The detection rate of depressive symptoms among students in Zhejiang Province was 19.92%; the rates were 17.20% in boys and 22.87% in girls( χ 2=164.89, P <0.05). The CES-D total score was 9.00(4.00,13.00). Multiple Logistic regression analysis revealed that loneliness had the strongest association with depressive symptoms ( AOR =9.58, 95% CI =8.90-10.30), while bullying exposure ( AOR =4.39, 95% CI =4.02-4.80), female students( AOR =1.81, 95% CI =1.68-1.94)，never eating breakfast ( AOR = 2.34，95% CI =2.00-2.67) and overweight/obesity( AOR =1.10，95% CI =1.08-1.12) were significant associated factors of depressive symptoms among students (all P <0.05). Analysis based on the XGBoost model produced highly consistent results, identifying the above 5 factors as the core features with the highest correlation strength (all P <0.05). Conclusions Female, loneliness, bullying exposure, frequency of weekly breakfast and BMI are strongly associated with depressive symptoms among students. Mental health education for high risk groups should be strengthened, and coordinated prevention efforts between families and schools are recommended.