Mapping the intellectual structure and landscape of colorectal cancer immunotherapy: A bibliometric analysis.

Immunotherapy, particularly immune checkpoint inhibitor (ICIs) therapy, stands as an innovative therapeutic approach currently garnering substantial attention in cancer treatment. It has become a focal point of numerous studies, showcasing significant potential in treating malignancies, including lung cancer and melanoma. The objective of this research is to analyze publications regarding immunotherapy for colorectal cancer (CRC), investigating their attributes and identifying the current areas of interest and cutting-edge advancements. We took into account the publications from 2002 to 2022 included in the Web of Science Core Collection. Bibliometric analysis and visualization were conducted using CiteSpace, VOSviewer, R-bibliometrix, and Microsoft Excel. The quantity of publications associated with this domain has been steadily rising over the years, encompassing 3753 articles and 1498 reviews originating from 573 countries and regions, involving 19,166 institutions, 1011 journals, and 32,301 authors. In this field, China, the United States, and Italy are the main countries that come forward for publishing. The journal with the greatest impact factor is CA-A Cancer Journal for Clinicians. Romain Cohen leads in the number of publications, while Le Dt stands out as the most influential author. The immune microenvironment and immune infiltration are emerging as key hotspots and future research directions in this domain. This research carries out an extensive bibliometric examination of immunotherapy for colorectal cancer, aiding researchers in understanding current focal points, investigating possible avenues for research, and recognizing forthcoming development trends.

A novel method for assessing cardiac function in patients with coronary heart disease based on wrist pulse analysis.

BACKGROUND: The timely assessment of B-type natriuretic peptide (BNP) marking chronic heart failure risk in patients with coronary heart disease (CHD) helps to reduce patients' mortality. OBJECTIVE: To evaluate the potential of wrist pulse signals for use in the cardiac monitoring of patients with CHD. METHODS: A total of 419 patients with CHD were assigned to Group 1 (BNP < 95 pg/mL, n = 249), 2 (95 < BNP < 221 pg/mL, n = 85), and 3 (BNP > 221 pg/mL, n = 85) according to BNP levels. Wrist pulse signals were measured noninvasively. Both the time-domain method and multiscale entropy (MSE) method were used to extract pulse features. Decision tree (DT) and random forest (RF) algorithms were employed to construct models for classifying three groups, and the models' performance metrics were compared. RESULTS: The pulse features of the three groups differed significantly, suggesting different pathological states of the cardiovascular system in patients with CHD. Moreover, the RF models outperformed the DT models in performance metrics. Furthermore, the optimal RF model was that based on a dataset comprising both time-domain and MSE features, achieving accuracy, average precision, average recall, and average F1-score of 90.900%, 91.048%, 90.900%, and 90.897%, respectively. CONCLUSIONS: The wrist pulse detection technology employed in this study is useful for assessing the cardiac function of patients with CHD.

Turfgrass-dependent mycotrophic change enhances soil deterioration in dry, cold and high-alkali environments.

AIMS: Soil quality is undergoing severe degradation under anthropogenic effects. Different methods of land management have been implemented for soil reclamation, such as turfing. Although widely accepted to improve soil quality, turfing in specific environments may also culminate in soil deterioration. We aim to know how turfing impacts soils by changing mycobiomes. METHODS AND RESULTS: The soil physicochemical properties and ITS metabarcoding were used to investigate mycobiome diversity and eco-function differences between the eudicot Dianthus plumarius and the monocot Poa pratensis in dry, cold, and high-alkali soil. The effects of plantation and the rhizosphere (e.g. root exudates) were tested. We showed that the change in soil mycobiomes in different planted bulk soils and rhizospheres could mainly be attributed to species turnover, with minor nestedness. Unexpectedly, the soil deteriorates more following turfing. The increasing saprotrophs in planted bulk soil were more marked in the monocot than in the eudicot, even the rhizosphere effect alleviated saprotrophic risks in the rhizosphere. CONCLUSIONS: Turfing deteriorates the health of high-alkali soil by reducing nitrification, and upshift the soil saprotrophs in a dry and cold environment.

The complete chloroplast genome sequence of Begonia arachnoidea (Begoniaceae).

There are more than 2035 Begonia species (Begoniaceae) reported currently in the world. Begonia arachnoidea was found as a new species within a small area in Southern China. In this study, we are reporting for the first time its chloroplast genome for the purpose to compare with the chloroplast genomic data from other plant taxa which were closely related to this new species. Our results show that the circular chloroplast genome of B. arachnoidea is 169,725 bp in length, with 35.49% GC content. The whole structure of the genome has 76,431 bp in a large single-copy (LSC) region, 18,146 bp in a small single-copy (SSC) region, and the two inverted repeat (IRs) regions are both 37,574 bp. There are 90 protein-coding genes, 8 rRNA genes, and 42 tRNA genes encoded in this genome. Final phylogenetic analysis revealed that B. arachnoidea is genetically closest to B. pulchrifolia and B. coptidifolia.

Physicochemical and Biotic Changes and the Phylogenetic Evenness of Microbial Community in Soil Subjected to Phytoreclamation.

Phytoreclamation is the intervention of plants to improve degraded soil quality, changing soil biotic and abiotic properties. Many studies have focused on microbial composition and bioactivity, but few explored the changes in phylogenetic assemblages of soil microbiota after phytoreclamation. This study compared microbiomes of bare land to those of planted soils and investigated how the rhizosphere environment affects microbial assemblages from monocot Poa pratensis and eudicot Dianthus plumarius plantings using 16S rRNA metabarcoding. The results showed that the biotic susceptibility of soil to the rhizosphere environment was higher than that of the abiotic. A noticeable change was in some soil physicochemical properties like Na, P, Zn, Cu, C, and sand-to-silt proportion before and after phytoreclamation, but not between the rhizosphere and bulk soil of plantings. Contrastingly, microbial composition and diversity were significantly affected by both turfing and rhizosphere effects and were more susceptible to differences in turfing or not than in planting species. In the turfgrass, the microbiome differences between plants were greater in the rhizosphere than in the surrounding bulk soil, indicating the proximal influence of root exudates. We also found that the main abiotic factors that influenced microbial composition were Na, Zn, NOx, N, and S; as for the phylogenetic assemblages, were by K levels and the increase of silt. Turfgrass decomposes soil aggregates and changes the physicochemical properties, thereby evens the phylogenetic clustering of the soil microbial community. We demonstrated that the deterministic process affects the microbial assemblage and acts as a selective agent of the soil microbiota in fundamental and realized niches. Phytoreclamation may lead to abiotic soil changes that reallocate resources to microbes. This could affect the phylogeny of the microbial assemblages and increase microbial richness.

Status and prospect of international standardization of TCM diagnosis.

The present study aimed to review the current status and development of international standards in the domain of traditional Chinese medicine (TCM) diagnosis. Moreover, the roles and relevant work of different organizations in developing such standards were explored, and the difficulties and challenges encountered were analyzed. The study further elaborated on the approaches to establish a complete set of international standards on TCM diagnosis. It also provided a promising solution for the development of international standards on TCM diagnosis.

[Research progress in original species identification in industry chain of Rhei Radix et Rhizoma].

Rhei Radix et Rhizoma is a kind of commonly used Chinese medicinal materials. Due to the overharvesting, the wild resource is endangering. Large market demand caused severely adulterant of commercial Rhei Radix et Rhizoma medicinal materials and decoction pieces. This manuscript reviewed the advances of the original species authentication in the industrial chain of Rhei Radix et Rhizoma during the latest decade, including characteristics and microscopic features, phytochemical analysis on anthraquinones, and molecular authentication based on DNA barcoding. Accordingly, an original species authentication route for the industrial chain of Rhei Radix et Rhizoma was summarized:(1)the identification of seeds and seedlings by DNA barcoding;(2) the selection of high variable sites based on the chloroplast genome;(3)biomonitoring of the Rhei Radix et Rhizoma medicinal materials and decoction pieces by two-dimensional DNA barcode;(4)traceability of Chinese patent medicines by third-generation sequencing. In conclusion, the combination of molecular identification and traditional identification methods provides a new idea for the identification of the original species of Rhei Radix et Rhizoma in the industrial chain and a essential guidance for the research of drug safety and efficacy of Rhei Radix et Rhizoma.

Identifying Coronary Artery Lesions by Feature Analysis of Radial Pulse Wave: A Case-Control Study.

BACKGROUND: Cardiovascular diseases have been always the most common cause of morbidity and mortality worldwide. Health monitoring of high-risk and suspected patients is essential. Currently, invasive coronary angiography is still the most direct and accurate method of determining the severity of coronary artery lesions, but it may not be the optimal clinical choice for suspected patients who had clinical symptoms of coronary heart disease (CHD) such as chest pain but no coronary artery lesion. Modern medical research indicates that radial pulse waves contain substantial pathophysiologic information about the cardiovascular and circulation systems; therefore, analysis of these waves could be a noninvasive technique for assessing cardiovascular disease. OBJECTIVE: The objective of this study was to analyze the radial pulse wave to construct models for assessing the extent of coronary artery lesions based on pulse features and investigate the latent value of noninvasive detection technology based on pulse wave in the evaluation of cardiovascular disease, so as to promote the development of wearable devices and mobile medicine. METHOD: This study included 529 patients suspected of CHD who had undergone coronary angiography. Patients were sorted into a control group with no lesions, a 1 or 2 lesion group, and a multiple (3 or more) lesion group as determined by coronary angiography. The linear time-domain features and the nonlinear multiscale entropy features of their radial pulse wave signals were compared, and these features were used to construct models for identifying the range of coronary artery lesions using the k-nearest neighbor (KNN), decision tree (DT), and random forest (RF) machine learning algorithms. The average precision of these algorithms was then compared. RESULTS: (1) Compared with the control group, the group with 1 or 2 lesions had increases in their radial pulse wave time-domain features H2/H1, H3/H1, and W2 (P < 0.05), whereas the group with multiple lesions had decreases in MSE1, MSE2, MSE3, MSE4, and MSE5 (P < 0.05). (2) Compared with the 1 or 2 lesion group, the multiple lesion group had increases in T1/T (P < 0.05) and decreases in T and W1 (P < 0.05). (3) The RF model for identifying numbers of coronary artery lesions had a higher average precision than the models built with KNN or DT. Furthermore, average precision of the model was highest (80.98%) if both time-domain features and multiscale entropy features of radial pulse signals were used to construct the model. CONCLUSION: Pulse wave signal can identify the range of coronary artery lesions with acceptable accuracy; this result is promising valuable for assessing the severity of coronary artery lesions. The technique could be used to development of mobile medical treatments or remote home monitoring systems for patients suspected or those at high risk of coronary atherosclerotic heart disease.

CRIF1 enhances p53 activity via the chromatin remodeler SNF5 in the HCT116 colon cancer cell lines.

CR6-interacting factor 1 (CRIF1) is ubiquitously expressed in human tissues. CRIF1 was first identified as a Gadd45γ (also known as CR6)-interacting protein, and it was also identified in a human colon cancer cell line stably transformed with p53. These results suggested that CRIF1 functions in the nucleus with p53 and Gadd45 family proteins in the suppression of cell growth and tumor development. Here, we found that CRIF1 could be recruited to a specific region in the promoter of the p53 gene, eliciting an increase in the mRNA and protein levels of p53 as well as p53 functional target genes. These functions required CRIF1 to interact with SNF5. CRIF1 was further recruited to the upstream promoter region of the p53 gene to suppress cell cycle progression in HCT116 cells. To our knowledge, this is the first evidence indicating that SNF5 is indispensable for CRIF1-enhanced p53 activity and its function in the suppression of cell cycle arrest in human cancer cells.

Classifying syndromes in Chinese medicine using multi-label learning algorithm with relevant features for each label.

OBJECTIVE: To develop an effective Chinese Medicine (CM) diagnostic model of coronary heart disease (CHD) and to confifirm the scientifific validity of CM theoretical basis from an algorithmic viewpoint. METHODS: Four types of objective diagnostic data were collected from 835 CHD patients by using a self-developed CM inquiry scale for the diagnosis of heart problems, a tongue diagnosis instrument, a ZBOX-I pulse digital collection instrument, and the sound of an attending acquisition system. These diagnostic data was analyzed and a CM diagnostic model was established using a multi-label learning algorithm (REAL). RESULTS: REAL was employed to establish a Xin (Heart) qi defificiency, Xin yang defificiency, Xin yin defificiency, blood stasis, and phlegm fifive-card CM diagnostic model, which had recognition rates of 80.32%, 89.77%, 84.93%, 85.37%, and 69.90%, respectively. CONCLUSIONS: The multi-label learning method established using four diagnostic models based on mutual information feature selection yielded good recognition results. The characteristic model parameters were selected by maximizing the mutual information for each card type. The four diagnostic methods used to obtain information in CM, i.e., observation, auscultation and olfaction, inquiry, and pulse diagnosis, can be characterized by these parameters, which is consistent with CM theory.

[Transcriptome characterization of Ephedra sinica with 454 ESTs].

Using the latest 454 GS FLX platform and Titanium regent, a substantial expressed sequence tag (ESTs) dataset of Ephedra sinica was produced, and the profile of gene expression and function gene of which were investigated. A total of 48 389 reads with an average length of 373 bp were generated. These 454 reads were assembled into 18 801 unigenes, which were all 454 sequencing identified. A total number of 10 531 unigenes(56.0%) were annotated using BLAST searches (E-value≤1×10⁻5) against the Nr, Nt, TAIR, SwissProt and KEGG databases. With respect to genes related to ephedrine biosynthesis, 19 unigenes(encoding 9 enzymes) were found. A total of 97 putative genes encoding cytochrome P450s were also discovered. Data presented in this study will provide an important resource for the scientific community that is interested in the functional genomics and secondary metabolism of E. sinica.

Pulse signal analysis of patients with coronary heart diseases using Hilbert-Huang transformation and time-domain method.

OBJECTIVE: To explore characteristic of pulse signal to distinguish patients with coronary heart diseases (CHD) from patients without CHD and healthy adults, and accordingly evaluate the potential role of pulse signal to diagnosis CHD. METHODS: Totally 407 patients enrolled from 4 collaborating medical centers were assigned to a CHD group (205 patients) and a non-CHD group (202 patients). The healthy control group (62 adults) enrolled from Shanghai University of Traditional Chinese Medicine. Pulse signals were collected using the synchronous multiplex pulse signal acquisition system. The pulse signals were analyzed and extracted using Hilbert-Huang transformation (HHT) and time-domain, respectively. The time-domain parameters of pulse signal were processed by the analysis of variance (SNK test). RESULTS: Special patterns in the CHD group pulse signal were found in this study: (1) time-domain parameters of pulse signal, h1, h3, h4, h3/h1, ts, t4/t were increased and w was wider; (2) 44% of C2 waves in HHT were chaotic and disordered and 72% of C waves were exhibited irregularly with average amplitude over 10 g-forces, which were all significantly different from controls. CONCLUSION: Characteristic wave and time-domain parameters of pulse signal were extracted using HHT and time-domain which could be served as a non-invasive approach for assessing patients with CHD.

Analysis of the diagnostic consistency of Chinese medicine specialists in cardiovascular disease cases and syndrome identification based on the relevant feature for each label learning method.

OBJECTIVE: To analyze the diagnostic consistency of Chinese medicine (CM) specialists in patients with cardiovascular disease and to study syndrome classification and identification based on the multi-label learning method. METHODS: Using self-developed CM clinical scales to collect cases, inquiry information, complexity, tongue manifestation and pulse manifestation were assessed. The number of cases collected was 2,218. Firstly, each case was differentiated by two CM specialists according to the same diagnostic criteria. The consistency of the diagnosis based on Cohen's Kappa coefficient was analyzed. Secondly, take the same diagnosis syndromes of two specialists as the results of the cases. According to injury information in the CM scale "yes" or "no" was assigned "1" or "0", and according to the syndrome type in each case "yes" or "no" was assigned "1" or "0". CM information data on cardiovascular disease cases were established. We studied CM syndrome classification and identification based on the relevant feature for each label (REAL) learning method, and the diagnostic rate of the syndrome was studied using the REAL method when the number of features selected was 5, 10, 15, 20, 30, 50, 70, and 100, respectively. RESULTS: The syndromes with good diagnostic consistency were Heart (Xin)-qi deficiency, Heart-yang deficiency, Heart-yin deficiency, phlegm, stagnation of blood and stagnation of qi. Syndromes with poor diagnostic consistency were heart-blood deficiency and blood deficiency of Heart and Liver (Gan). The highest diagnostic rates using the REAL method were Heart-yang deficiency followed by Heart-qi deficiency. A different number of features, such as 5, 10, 15, 20, 30, 40, 50, 70, and 100, respectively, were selected and the diagnostic accuracy based on five features showed the highest diagnostic accuracy. The top five features which had a strong correlation with the syndromes were in accordance with the CM theory. CONCLUSIONS: CM syndrome differentiation is strongly subjective and it is difficult to obtain good diagnostic consistency. The REAL method fully considers the relationship between syndrome types and injury symptoms, and is suitable for the establishment of models for CM syndrome classification and identification. This method can probably provide the prerequisite for objectivity and standardization of CM differentiation.

Objective Auscultation of TCM Based on Wavelet Packet Fractal Dimension and Support Vector Machine.

This study was conducted to illustrate that auscultation features based on the fractal dimension combined with wavelet packet transform (WPT) were conducive to the identification the pattern of syndromes of Traditional Chinese Medicine (TCM). The WPT and the fractal dimension were employed to extract features of auscultation signals of 137 patients with lung Qi-deficient pattern, 49 patients with lung Yin-deficient pattern, and 43 healthy subjects. With these features, the classification model was constructed based on multiclass support vector machine (SVM). When all auscultation signals were trained by SVM to decide the patterns of TCM syndromes, the overall recognition rate of model was 79.49%; when male and female auscultation signals were trained, respectively, to decide the patterns, the overall recognition rate of model reached 86.05%. The results showed that the methods proposed in this paper were effective to analyze auscultation signals, and the performance of model can be greatly improved when the distinction of gender was considered.

New oleanane-type triterpenoid saponins isolated from the seeds of Celosia argentea.

Three new oleanane-type triterpenoid saponins named celosins H, I, and J were isolated from the seeds of Celosia argentea L. Their structures were characterized as 3-O-ß-D-xylopyranosyl-(1 → 3)-ß-D-glucuronopyranosyl-polygalagenin 28-O-ß-D-glucopyranosyl ester, 3-O-ß-D-glucuronopyranosyl-medicagenic acid 28-O-ß-D-xylcopyranosyl-(1 → 4)-α-L-rhamnopyranosyl-(1 → 2)-ß-D-fucopyranosyl ester, and 3-O-ß-D-glucuronopyranosyl-medicagenic acid 28-O-α-L-arabinopyranosyl-(1 → 3)-[ß-D-xylcopyranosyl-(1 → 4)]-α-L-rhamnopyranosyl-(1 → 2)-ß-D-fucopyranosyl ester by NMR, MS, and chemical evidences, respectively. In our opinion, celosins H-J could be used as chemical markers for the quality control of C. argentea seeds.

Research on zheng classification fusing pulse parameters in coronary heart disease.

This study was conducted to illustrate that nonlinear dynamic variables of Traditional Chinese Medicine (TCM) pulse can improve the performances of TCM Zheng classification models. Pulse recordings of 334 coronary heart disease (CHD) patients and 117 normal subjects were collected in this study. Recurrence quantification analysis (RQA) was employed to acquire nonlinear dynamic variables of pulse. TCM Zheng models in CHD were constructed, and predictions using a novel multilabel learning algorithm based on different datasets were carried out. Datasets were designed as follows: dataset1, TCM inquiry information including inspection information; dataset2, time-domain variables of pulse and dataset1; dataset3, RQA variables of pulse and dataset1; and dataset4, major principal components of RQA variables and dataset1. The performances of the different models for Zheng differentiation were compared. The model for Zheng differentiation based on RQA variables integrated with inquiry information had the best performance, whereas that based only on inquiry had the worst performance. Meanwhile, the model based on time-domain variables of pulse integrated with inquiry fell between the above two. This result showed that RQA variables of pulse can be used to construct models of TCM Zheng and improve the performance of Zheng differentiation models.

[Metabolite changes in the greasy tongue coating of patients with chronic gastritis].

OBJECTIVE: To explore the changes in metabolites in the greasy tongue coating in patients with chronic gastritis. METHODS: Forty chronic gastritis patients presenting with greasy tongue coating, 30 chronic gastritis patients presenting with non-greasy tongue coating, and 20 healthy control persons presenting with light red tongues and thin white coating were enrolled, and the tongue coating was detected by combining artificial diagnosis and the Z-BOX Tongue Digital Analyzer's diagnosis. Samples of all the tongue coatings were collected before treatment. The metabolic fingerprinting of the tongue coating samples was obtained using ultra-performance liquid chromatography and mass spectrometry (UPLC-MS), and the metabolic components in the tongue coating samples were detected. After this, principal component analysis, partial least squares discriminant analysis and orthogonal partial least squares discriminant analysis (OPLS-DA) were used to identify potential metabolic markers. Finally, the components were identified using the Chemspider and HMDB searching. RESULTS: UPLC-MS results were analyzed by OPLS-DA and showed that the metabolites among the three groups were distributed in different regions. The different potential metabolic markers between the patients with or without greasy coating were 3-ketolactose, 2-deoxy-D-ribose, UDP-D-galactose metarhodopsin, ascorbate, picolinate and histidine. The different potential metabolic markers between the greasy coating group and the normal group were 3-ketolactose, UDP-D-galactose, leukotriene A4 and vitamin D(2). CONCLUSION: The metabolites of the greasy coating group, the non-greasy coating group and the normal group show significant differences in energy metabolism, mainly of glucose metabolism. This demonstrated that glucose metabolism may be one of the mechanisms leading to the formation of greasy coating.

Nonlinear Analysis of Auscultation Signals in TCM Using the Combination of Wavelet Packet Transform and Sample Entropy.

Auscultation signals are nonstationary in nature. Wavelet packet transform (WPT) has currently become a very useful tool in analyzing nonstationary signals. Sample entropy (SampEn) has recently been proposed to act as a measurement for quantifying regularity and complexity of time series data. WPT and SampEn were combined in this paper to analyze auscultation signals in traditional Chinese medicine (TCM). SampEns for WPT coefficients were computed to quantify the signals from qi- and yin-deficient, as well as healthy, subjects. The complexity of the signal can be evaluated with this scheme in different time-frequency resolutions. First, the voice signals were decomposed into approximated and detailed WPT coefficients. Then, SampEn values for approximated and detailed coefficients were calculated. Finally, SampEn values with significant differences in the three kinds of samples were chosen as the feature parameters for the support vector machine to identify the three types of auscultation signals. The recognition accuracy rates were higher than 90%.

Association study of ACE polymorphisms and systemic lupus erythematosus in Northern Chinese Han population.

Systemic lupus erythematosus (SLE) is an autoimmune disease, with multiple genetic and environmental factors involving in its etiology. Angiotensin converting enzyme (ACE) gene was reported to have important roles in the development and progression of SLE. In this study, a case-control study was carried out to investigate the effects of seven SNPs and I/D in ACE gene in the development of SLE in Northern China. Seven SNPs including A5466C, T3892C, A240T, C1237T, G2215A, A2350G and C3409T were genotyped by PCR-RFLP method, and I/D was examined by agarose gel electrophoresis followed PCR directly. 314 SLE patients were compared to 320 normal controls in the study. Data were analyzed by SPSS 13.0 and HaploView software. The frequency distribution of SNP A2350G and Alu I/D and five haplotypes (AAAACCCI, AGAACCTD, AAAATCTI, TAAATTTI and TAAATCTI) were demonstrated to be different between case and control groups significantly. Whereas other SNPs and haplotypes had no differences in two cohorts. The results revealed that variations of ACE gene had association with SLE, which indicated ACE gene may play an important role in pathogenesis of SLE in Northern Chinese Han population.

Human PIH1 associates with histone H4 to mediate the glucose-dependent enhancement of pre-rRNA synthesis.

Ribosome biogenesis is critical in the growth of eukaryotic cells, in which the synthesis of precursor ribosomal RNA is the first and rate-limiting step. Here, we show that human PIH1 domain-containing protein 1 (PIH1) interacts directly with histone H4 and recruits the Brg1-SWI/SNF complex via SNF5 to human rRNA genes. This process is likely involved in PIH1-dependent DNase I-hypersensitive chromatin remodeling at the core promoter of the rRNA genes. PIH1 mediates the occupancy of not only the Brg1 complex but also the Pol I complex at the core promoter and enhances transcription initiation of rRNA genes. Additionally, the interaction between PIH1 and H4K16 expels TIP5, a component of the silencing nucleolar remodeling complex (NoRC), from the core region, suggesting that PIH1 is involved in the derepression of NoRC-silenced rRNA genes. These data indicate that PIH1 is a positive regulator of human rRNA genes and is of great importance for the recovery of human cells from nutrient starvation and the transition to glucose-induced exponential growth in vivo.