Wide-field illumination diffuse optical tomography within a framework of single-pixel time-domain spatial frequency domain imaging.

We present a wide-field illumination time-domain (TD) diffusion optical tomography (DOT) for three-dimensional (3-D) reconstruction within a shallow region under the illuminated surface of the turbid medium. The methodological foundation is laid on the single-pixel spatial frequency domain (SFD) imaging that facilitates the adoption of the well-established time-correlated single-photon counting (TCSPC)-based TD detection and generalized pulse spectrum techniques (GPST)-based reconstruction. To ameliorate the defects of the conventional diffusion equation (DE) in the forward modeling of TD-SFD-DOT, mainly the low accuracy in the near-field region and in profiling early-photon migration, we propose a modified model employing the time-dependent δ-P1 approximation and verify its improved accuracy in comparison with both the Monte Carlo and DE-based ones. For a simplified inversion process, a modified GPST approach is extended to TD-SFD-DOT that enables the effective separation of the absorption and scattering coefficients using a steady-state equivalent strategy. Furthermore, we set up a single-pixel TD-SFD-DOT system that employs the TCSPC-based TD detection in the SFD imaging framework. For assessments of the reconstruction approach and the system performance, phantom experiments are performed for a series of scenarios. The results show the effectiveness of the proposed methodology for rapid 3-D reconstruction of the absorption and scattering coefficients within a depth range of about 5 mean free pathlengths.

Application of Hospital-Community-Family "Trinity" Remote Rehabilitation Guidance Based on Internet + WeChat Platform in Patients with Stroke After Discharge.

Objective: To investigate the impact of an Internet + WeChat platform-based "trinity" remote rehabilitation model involving the hospital, community, and family on stroke patient rehabilitation nursing. Methods: 159 patients with stroke who were discharged from Beijing Luhe Hospital of Capital Medical University from January 1, 2018, to December 31, 2019, were selected and divided into a control group (79 cases) and an experimental group (80 cases) by the random drawing method. The control group was given routine nursing, and the experimental group was given remote rehabilitation nursing intervention by using the WeChat network platform based on the control group. Limb function [Fugl-Meyer Assessment Scale (FMA)] and activities of daily living [Modified Barthel Index (MBI)] were evaluated at enrollment and at the end of 3 months, 6 months and 12 months in both groups. The compliance and satisfaction surveys in the two groups were evaluated after 6 months and 12 months of intervention. Results: (1) Before the intervention, there was no statistical significance in FMA score between the two groups (t = 0.798, P > .05). After 3 months, 6 months and 12 months of intervention, the FMA score in the two groups was increased compared with that before intervention (t = 2.463, P < .05), and the FMA scores in the experimental group at the above time points were higher than those in the control group (ts = 7.057, 14.285, Ps < .05). (2) There was no statistical difference in MBI scores between the two groups before intervention (t = 0.798, P > .05). After 3 months, 6 months, and 12 months of intervention, the MBI score in the two groups was increased compared with that before intervention (t = 0.232, P < .05), and MBI scores in the experimental group at the above time points were higher compared to the control group (ts = 4.959, 8.842, 8.131, Ps < .05). (3) The compliance scores in the experimental group were higher than those in the control group after 6 months and 12 months of intervention (ts = 4.959, 8.842, 8.131, Ps < .05). (4) The satisfaction survey scores in the experimental group after 6 months and 12 months of intervention were higher than those in the control group (ts = 2.120 ~ 14.554, Ps < .05). Conclusion: The Hospital-community-family "trinity" stroke rehabilitation model on the WeChat network platform holds significant importance. Enhancing limb function and daily living for stroke patients improves their quality of life and lessens reliance on caregivers. This positively impacts both survivors' well-being and healthcare resources. Increased patient satisfaction and compliance suggest a potential revolution in post-stroke care, favoring a more patient-centered approach. Overall, this model has transformative potential for stroke treatment, offering holistic and patient-focused strategies. Its success promises better rehabilitation outcomes, patient satisfaction, and cost reduction, while paving the way for innovative research in stroke treatment and rehabilitation.

A CRISPR-Cas12a-based electrochemical biosensor for the detection of microphthalmia-associated transcription factor.

A novel electrochemical biosensor that combines the CRISPR-Cas12a system with a gold electrode is reported for the rapid and sensitive detection of microphthalmia-associated transcription factor (MITF). The biosensor consists of a gold electrode modified with DNA1, which contains the target sequence of MITF and is labeled with ferrocene, an electroactive molecule. The biosensor also includes hairpin DNA, which has a binding site for MITF and can hybridize with helper DNA to form a double-stranded complex that activates CRISPR-Cas12a. When MITF is present, it binds to hairpin DNA and prevents its hybridization with helper DNA, thus inhibiting CRISPR-Cas12a activity and preserving the DPV signal of ferrocene. When MITF is absent, hairpin DNA hybridizes with helper DNA and activates CRISPR-Cas12a, which cleaves DNA1 and releases ferrocene, thus reducing the DPV signal. The biosensor can detect MITF with high sensitivity (with an LOD of 8.14 fM), specificity, and accuracy in various samples, such as cell nuclear extracts and human serum. The biosensor can also diagnose and monitor melanocyte-related diseases and melanin production. This work provides a simple, fast, sensitive, and cost-effective biosensor for MITF detection and a valuable tool for applications in genetic testing, disease diagnosis, and drug screening.

Tikhonov regularization-based extended Kalman filter technique for robust and accurate reconstruction in diffuse optical tomography.

Diffuse optical tomography (DOT) is a non-invasive imaging modality that uses near-infrared light to probe the optical properties of tissue. In conventionally used deterministic methods for DOT inversion, the measurement errors were not taken into account, resulting in unsatisfactory noise robustness and, consequently, affecting the DOT image reconstruction quality. In order to overcome this defect, an extended Kalman filter (EKF)-based DOT reconstruction algorithm was introduced first, which improved the reconstruction results by incorporating a priori information and measurement errors to the model. Further, to mitigate the instability caused by the ill-condition of the observation matrix in the tomographic imaging problem, a new, to the best of our knowledge, estimation algorithm was derived by incorporating Tikhonov regularization to the EKF method. To verify the effectiveness of the EKF algorithm and Tikhonov regularization-based EKF algorithm for DOT imaging, a series of numerical simulations and phantom experiments were conducted, and the experimental results were quantitatively evaluated and compared with two conventionally used deterministic methods involving the algebraic reconstruction technique and Levenberg-Marquardt algorithm. The results show that the two EKF-based algorithms can accurately estimate the location and size of the target, and the imaging accuracy and noise robustness are obviously improved. Furthermore, the Tikhonov regularization-based EKF obtained optimal parameter estimations, especially under the circumstance of low absorption contrast (1.2) and high noise level (10%).

Suppressing physiological interferences and physical noises in functional diffuse optical tomography via tandem inversion filtering and LSTM classification.

For performance enhancement of functional diffuse optical tomography (fDOT), we propose a tandem method that takes advantage of the inversion filtering and the long short term memory (LSTM) classification to simultaneously suppress the physiological interferences and physical noises in fDOT. In the former phase, the absorption perturbation maps over the scalp-skull (SS) and cerebral-cortex (CC) layers are firstly pre-reconstructed using a two-layer topography scheme. Then, the recovered SS-map is inversed into measurement space by the forward calculation to estimate the intensity changes associated with the physiological interferences. Finally, the raw measurements are adaptively filtered with reference to the estimated intensity changes for accomplishing the model-based full three-dimension (3D) reconstruction. In the later phase, for further removing the randomly distributed physical noises, mainly instrumental noise, a LSTM network based fusion strategy is applied, where a pixel-wise binary mask of "activated" or "inactive" state is generated by performing LSTM classification and then fused with the 3D reconstruction. The results of the simulative investigation and in-vivo experiment show the proposed tandem scheme achieves improved performance in fDOT using a cost-effective and physically explicable way. Thus, the proposed method can be promisingly applied in real-time neuroimaging to acquire cortical neural activation information with improved reliability, quantification and resolution.

Contrast-induced encephalopathy with significantly elevated levels of cerebrospinal fluid protein.

Contrast-induced encephalopathy (CIE) is a rare complication of angiography. According to our knowledge, the majority of CIE reports is imaging observations and rarely includes results of cerebrospinal fluid (CSF) tests. Furthermore, among the cases reporting the data for CSF testing, most of the results were normal. Here, we report a case of CIE presenting with significantly elevated levels of CSF protein. We found that the course of improvement in brain imaging findings was not consistent with the severity of clinical manifestations. The diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) sequences were normal. Considering the lack of convenient direct indicators to observe blood-brain barrier (BBB) function, changes in the levels of CSF protein may be related to BBB permeability and recovery and may serve as a potential prognostic marker.

Adsorption and dehydrogenation of C2-C6n-alkanes over a Pt catalyst: a theoretical study on the size effects of alkane molecules and Pt substrates.

Adsorption and dehydrogenation of C2-C6n-alkanes are investigated on a Pt substrate using density functional theory (DFT) calculations, and the size effects of alkane molecules and Pt substrates are discussed in detail. The Pt(111) surface and Pt55 cluster are chosen to represent large and small Pt nanoparticles, respectively. The C2-C6 straight-chain alkanes show no site preference on Pt(111) drifting over the surface, but prefer to locate along the edge sites of Pt55. Our results suggest that a linear relationship holds for the adsorption energies of n-alkanes against the chain length on Pt(111), in accordance with the experimental observations. Pt55 also exhibits a similar linear relationship for n-alkanes but with larger adsorption energies due to the low-coordinated Pt atoms at the edge site. For the two-step dehydrogenation from alkanes to alkenes, the first dehydrogenation reaction is the rate-determining step (RDS) on Pt(111), and a larger size of alkane molecule will lead to a lower dehydrogenation activity. While on Pt55, no RDS is present and the dehydrogenation activity oscillates slightly as the chain length of n-alkane increases. Generally, Pt55 involves lower energy barriers for most dehydrogenation steps compared to Pt(111), indicating that small Pt particles with more low-coordinated Pt atoms are more active towards alkane dehydrogenation. In addition, a clear BEP relationship is identified for all the dehydrogenation reactions of C2-C6n-alkanes on Pt substrates, and this linear relationship is independent of the particle size of the Pt substrate and the chain length of alkanes.

Genomic insights into mite phylogeny, fitness, development, and reproduction.

BACKGROUND: Predatory mites (Acari: Phytoseiidae) are the most important beneficial arthropods used in augmentative biological pest control of protected crops around the world. However, the genomes of mites are far less well understood than those of insects and the evolutionary relationships among mite and other chelicerate orders are contested, with the enigmatic origin of mites at one of the centres in discussion of the evolution of Arachnida. RESULTS: We here report the 173 Mb nuclear genome (from 51.75 Gb pairs of Illumina reads) of the predatory mite, Neoseiulus cucumeris, a biocontrol agent against pests such as mites and thrips worldwide. We identified nearly 20.6 Mb (~ 11.93% of this genome) of repetitive sequences and annotated 18,735 protein-coding genes (a typical gene 2888 bp in size); the total length of protein-coding genes was about 50.55 Mb (29.2% of this assembly). About 37% (6981) of the genes are unique to N. cucumeris based on comparison with other arachnid genomes. Our phylogenomic analysis supported the monophyly of Acari, therefore rejecting the biphyletic origin of mites advocated by other studies based on limited gene fragments or few taxa in recent years. Our transcriptomic analyses of different life stages of N. cucumeris provide new insights into genes involved in its development. Putative genes involved in vitellogenesis, regulation of oviposition, sex determination, development of legs, signal perception, detoxification and stress-resistance, and innate immune systems are identified. CONCLUSIONS: Our genomics and developmental transcriptomics analyses of N. cucumeris provide invaluable resources for further research on the development, reproduction, and fitness of this economically important mite in particular and Arachnida in general.

A Kalman-based tomographic scheme for directly reconstructing activation levels of brain function.

In functional near-infrared spectroscopy (fNIRS), the conventional indirect approaches first separately recover the spatial distribution of the changes in the optical properties at every time point, and then extract the activation levels by a time-course analysis process at every site. In the tomographic implementation of fNIRS, i.e., diffuse optical tomography (DOT), these approaches not only suffer from the ill-posedness of the optical inversions and error propagation between the two successive steps, but also fail to achieve satisfactory temporal resolution due to the requirement for a complete data set. To cope with the above adversities of the indirect approaches, we propose herein a direct approach to tomographically reconstructing the activation levels by incorporating a Kalman scheme. Dynamic simulative and phantom experiments were conducted for the performance validation of the proposed approach, demonstrating its potentials to improve the calculated images and to relax the speed limitation of the instruments.

Sparsity-regularized approaches to directly reconstructing hemodynamic response in brain functional diffuse optical tomography.

In brain functional diffuse optical tomography, conventional indirect approaches first separately reconstruct the spatial changes in the absorption coefficients at every time point and then calculate the spatial excited levels in terms of hemodynamic models. Direct approaches combine the two steps necessary in the indirect approaches and obtain the spatial excited levels directly. Although reconstruction quality has been improved by the direct approaches to some extent, they still lack sharp edges and suffer from low spatial resolution because of the ill-posedness of the inverse problems. In this paper, a priori sparsity is introduced to obtain the sparse solutions and further improve reconstruction quality. Simulation experiments are conducted to illustrate the expected performance improvements of the proposed approaches.

The pomegranate (Punica granatum L.) genome provides insights into fruit quality and ovule developmental biology.

Pomegranate (Punica granatum L.) has an ancient cultivation history and has become an emerging profitable fruit crop due to its attractive features such as the bright red appearance and the high abundance of medicinally valuable ellagitannin-based compounds in its peel and aril. However, the limited genomic resources have restricted further elucidation of genetics and evolution of these interesting traits. Here, we report a 274-Mb high-quality draft pomegranate genome sequence, which covers approximately 81.5% of the estimated 336-Mb genome, consists of 2177 scaffolds with an N50 size of 1.7 Mb and contains 30 903 genes. Phylogenomic analysis supported that pomegranate belongs to the Lythraceae family rather than the monogeneric Punicaceae family, and comparative analyses showed that pomegranate and Eucalyptus grandis share the paleotetraploidy event. Integrated genomic and transcriptomic analyses provided insights into the molecular mechanisms underlying the biosynthesis of ellagitannin-based compounds, the colour formation in both peels and arils during pomegranate fruit development, and the unique ovule development processes that are characteristic of pomegranate. This genome sequence provides an important resource to expand our understanding of some unique biological processes and to facilitate both comparative biology studies and crop breeding.

Loci and candidate genes conferring resistance to soybean cyst nematode HG type 2.5.7.

BACKGROUND: Soybean (Glycine max L. Merr.) cyst nematode (SCN, Heterodera glycines I,) is a major pest of soybean worldwide. The most effective strategy to control this pest involves the use of resistant cultivars. The aim of the present study was to investigate the genome-wide genetic architecture of resistance to SCN HG Type 2.5.7 (race 1) in landrace and elite cultivated soybeans. RESULTS: A total of 200 diverse soybean accessions were screened for resistance to SCN HG Type 2.5.7 and genotyped through sequencing using the Specific Locus Amplified Fragment Sequencing (SLAF-seq) approach with a 6.14-fold average sequencing depth. A total of 33,194 SNPs were identified with minor allele frequencies (MAF) over 4%, covering 97% of all the genotypes. Genome-wide association mapping (GWAS) revealed thirteen SNPs associated with resistance to SCN HG Type 2.5.7. These SNPs were distributed on five chromosomes (Chr), including Chr7, 8, 14, 15 and 18. Four SNPs were novel resistance loci and nine SNPs were located near known QTL. A total of 30 genes were identified as candidate genes underlying SCN resistance. CONCLUSIONS: A total of sixteen novel soybean accessions were identified with significant resistance to HG Type 2.5.7. The beneficial alleles and candidate genes identified by GWAS might be valuable for improving marker-assisted breeding efficiency and exploring the molecular mechanisms underlying SCN resistance.

Loci and candidate gene identification for resistance to Sclerotinia sclerotiorum in soybean (Glycine max L. Merr.) via association and linkage maps.

Soybean white mold (SWM), caused by Sclerotinia sclerotiorum ((Lib.) W. Phillips), is currently considered to be the second most important cause of soybean yield loss due to disease. Research is needed to identify SWM-resistant germplasm and gain a better understanding of the genetic and molecular basis of SWM resistance in soybean. Stem pigmentation after treatment with oxaloacetic acid is an effective indicator of resistance to SWM. A total of 128 recombinant inbred lines (RILs) derived from a cross of 'Maple Arrow' (partial resistant to SWM) and 'Hefeng 25' (susceptible) and 330 diverse soybean cultivars were screened for the soluble pigment concentration of their stems, which were treated with oxalic acid. Four quantitative trait loci (QTLs) underlying soluble pigment concentration were detected by linkage mapping of the RILs. Three hundred and thirty soybean cultivars were sequenced using the whole-genome encompassing approach and 25 179 single-nucleotide polymorphisms (SNPs) were detected for the fine mapping of SWM resistance genes by genome-wide association studies. Three out of five SNP markers representing a linkage disequilibrium (LD) block and a single locus on chromosome 13 (Gm13) were significantly associated with the soluble pigment content of stems. Three more SNPs that represented three minor QTLs for the soluble pigment content of stems were identified on another three chromosomes by association mapping. A major locus with the largest effect on Gm13 was found both by linkage and association mapping. Four potential candidate genes involved in disease response or the anthocyanin biosynthesis pathway were identified at the locus near the significant SNPs (<60 kbp). The beneficial allele and candidate genes should be useful in soybean breeding for improving resistance to SWM.

Domestication footprints anchor genomic regions of agronomic importance in soybeans.

Present-day soybeans consist of elite cultivars and landraces (Glycine max, fully domesticated (FD)), annual wild type (Glycine soja, nondomesticated (ND)), and semi-wild type (semi-domesticated (SD)). FD soybean originated in China, although the details of its domestication history remain obscure. More than 500 diverse soybean accessions were sequenced using specific-locus amplified fragment sequencing (SLAF-seq) to address fundamental questions regarding soybean domestication. In total, 64,141 single nucleotide polymorphisms (SNPs) with minor allele frequencies (MAFs) > 0.05 were found among the 512 tested accessions. The results indicated that the SD group is not a hybrid between the FD and ND groups. The initial domestication region was pinpointed to central China (demarcated by the Great Wall to the north and the Qinling Mountains to the south). A total of 800 highly differentiated genetic regions and > 140 selective sweeps were identified, and these were three- and twofold more likely, respectively, to encompass a known quantitative trait locus (QTL) than the rest of the soybean genome. Forty-three potential quantitative trait nucleotides (QTNs; including 15 distinct traits) were identified by genome-wide association mapping. The results of the present study should be beneficial for soybean improvement and provide insight into the genetic architecture of traits of agronomic importance.

Genetic characteristics of soybean resistance to HG type 0 and HG type 1.2.3.5.7 of the cyst nematode analyzed by genome-wide association mapping.

BACKGROUND: Soybean cyst nematode (SCN, Heterodera glycines Ichinohe) is one of the most fatal pests of soybean (Glycine max (L.) Merr.) worldwide and causes huge loss of soybean yield each year. Multiple sources of resistance are urgently needed for effective management of SCN via the development of resistant cultivars. The aim of the present study was to investigate the genetic architecture of resistance to SCN HG Type 0 (race 3) and HG Type 1.2.3.5.7 (race 4) in landraces and released elite soybean cultivars mostly from China. RESULTS: A total of 440 diverse soybean landraces and elite cultivars were screened for resistance to SCN HG Type 0 and HG Type 1.2.3.5.7. Exactly 131 new sources of SCN resistance were identified. Lines were genotyped by SNP markers detected by the Specific Locus Amplified Fragment Sequencing (SLAF-seq) approach. A total of 36,976 SNPs were identified with minor allele frequencies (MAF) > 4% that were present in 97% of all the genotypes. Genome-wide association mapping showed that a total of 19 association signals were significantly related to the resistance for the two HG Types. Of the 19 association signals, eight signals overlapped with reported QTL including Rhg1 and Rhg4 genes. Another eight were located in the linked regions encompassing known QTL. Three QTL were found that were not previously reported. The average value of female index (FI) of soybean accessions with resistant alleles was significantly lower than those with susceptible alleles for each peak SNP. Disease resistance proteins with leucine rich regions, cytochrome P450s, protein kinases, zinc finger domain proteins, RING domain proteins, MYB and WRKY transcription activation families were identified. Such proteins may participate in the resistant reaction to SCN and were frequently found in the tightly linked genomic regions of the peak SNPs. CONCLUSIONS: GWAS extended understanding of the genetic architecture of SCN resistance in multiple genetic backgrounds. Nineteen association signals were obtained for the resistance to the two Hg Types of SCN. The multiple beneficial alleles from resistant germplasm sources will be useful for the breeding of cultivars with improved resistance to SCN. Analysis of genes near association signals may facilitate the recognition of the causal gene(s) underlying SCN resistances.

The diploid genome sequence of an Asian individual.

Here we present the first diploid genome sequence of an Asian individual. The genome was sequenced to 36-fold average coverage using massively parallel sequencing technology. We aligned the short reads onto the NCBI human reference genome to 99.97% coverage, and guided by the reference genome, we used uniquely mapped reads to assemble a high-quality consensus sequence for 92% of the Asian individual's genome. We identified approximately 3 million single-nucleotide polymorphisms (SNPs) inside this region, of which 13.6% were not in the dbSNP database. Genotyping analysis showed that SNP identification had high accuracy and consistency, indicating the high sequence quality of this assembly. We also carried out heterozygote phasing and haplotype prediction against HapMap CHB and JPT haplotypes (Chinese and Japanese, respectively), sequence comparison with the two available individual genomes (J. D. Watson and J. C. Venter), and structural variation identification. These variations were considered for their potential biological impact. Our sequence data and analyses demonstrate the potential usefulness of next-generation sequencing technologies for personal genomics.

Computationally-efficient linear scheme for overlap time-gating spatial frequency domain diffuse optical tomography using an analytical diffusion model.

Time-domain (TD) spatial frequency domain (SFD) diffuse optical tomography (DOT) potentially enables laminar tomography of both the absorption and scattering coefficients. Its full time-resolved-data scheme is expected to enhance performances of the image reconstruction but poses heavy computational costs and also susceptible signal-to-noise ratio (SNR) limits, as compared to the featured-data one. We herein propose a computationally-efficient linear scheme of TD-SFD-DOT, where an analytical solution to the TD phasor diffusion equation for semi-infinite geometry is derived and used to formulate the Jacobian matrices with regard to overlap time-gating data of the time-resolved measurement for improved SNR and reduced redundancy. For better contrasting the absorption and scattering and widely adapted to practically-available resources, we develop an algebraic-reconstruction-technique-based two-step linear inversion procedure with support of a balanced memory-speed strategy and multi-core parallel computation. Both simulations and phantom experiments are performed to validate the effectiveness of the proposed TD-SFD-DOT method and show an achieved tomographic reconstruction at a relative depth resolution of ∼4 mm.

Analysis of lymph node metastasis and survival prognosis in early gastric cancer patients: A retrospective study.

BACKGROUND: Early gastric cancer (EGC) is a common malignant tumor of the digestive system, and its lymph node metastasis and survival prognosis have been concerning. By retrospectively analyzing the clinical data of EGC patients, we can better understand the status of lymph node metastasis and its impact on survival and prognosis. AIM: To evaluate the prognosis of EGC patients and the factors that affect lymph node metastasis. METHODS: The clinicopathological data of 1011 patients with EGC admitted to our hospital between January 2015 and December 2023 were collected in a retrospective cohort study. There were 561 males and 450 females. The mean age was 58 ± 11 years. The patient underwent radical gastrectomy. The status of lymph node metastasis in each group was determined according to the pathological examination results of surgical specimens. The outcomes were as follows: (1) Lymph node metastasis in EGC patients; (2) Analysis of influencing factors of lymph node metastasis in EGC; and (3) Analysis of prognostic factors in patients with EGC. Normally distributed measurement data are expressed as mean ± SD, and a t test was used for comparisons between groups. The data are expressed as absolute numbers or percentages, and the chi-square test was used for comparisons between groups. Rank data were compared using a nonparametric rank sum test. A log-rank test and a logistic regression model were used for univariate analysis. A logistic stepwise regression model and a Cox stepwise regression model were used for multivariate analysis. The Kaplan-Meier method was used to calculate the survival rate and construct survival curves. A log-rank test was used for survival analysis. RESULTS: Analysis of influencing factors of lymph node metastasis in EGC. The results of the multifactor analysis showed that tumor length and diameter, tumor site, tumor invasion depth, vascular thrombus, and tumor differentiation degree were independent influencing factors for lymph node metastasis in patients with EGC (odds ratios = 1.80, 1.49, 2.65, 5.76, and 0.60; 95%CI: 1.29-2.50, 1.11-2.00, 1.81-3.88, 3.87-8.59, and 0.48-0.76, respectively; P < 0.05). Analysis of prognostic factors in patients with EGC. All 1011 patients with EGC were followed up for 43 (0-13) months. The 3-year overall survival rate was 97.32%. Multivariate analysis revealed that age > 60 years and lymph node metastasis were independent risk factors for prognosis in patients with EGC (hazard ratio = 9.50, 2.20; 95%CI: 3.31-27.29, 1.00-4.87; P < 0.05). Further analysis revealed that the 3-year overall survival rates of gastric cancer patients aged > 60 years and ≤ 60 years were 99.37% and 94.66%, respectively, and the difference was statistically significant (P < 0.05). The 3-year overall survival rates of patients with and without lymph node metastasis were 95.42% and 97.92%, respectively, and the difference was statistically significant (P < 0.05). CONCLUSION: The lymph node metastasis rate of EGC patients was 23.64%. Tumor length, tumor site, tumor infiltration depth, vascular cancer thrombin, and tumor differentiation degree were found to be independent factors affecting lymph node metastasis in EGC patients. Age > 60 years and lymph node metastasis are independent risk factors for EGC prognosis.

Deep-learning approach to stratified reconstructions of tissue absorption and scattering in time-domain spatial frequency domain imaging.

Significance: The conventional optical properties (OPs) reconstruction in spatial frequency domain (SFD) imaging, like the lookup table (LUT) method, causes OPs aliasing and yields only average OPs without depth resolution. Integrating SFD imaging with time-resolved (TR) measurements enhances space-TR information, enabling improved reconstruction of absorption (µa) and reduced scattering (µs') coefficients at various depths. Aim: To achieve the stratified reconstruction of OPs and the separation between µa and µs', using deep learning workflow based on the temporal and spatial information provided by time-domain SFD imaging technique, while enhancing the reconstruction accuracy. Approach: Two data processing methods are employed for the OPs reconstruction with TR-SFD imaging, one is full TR data, and the other is the featured data extracted from the full TR data (E, continuous-wave component, ⟨t⟩, mean time of flight). We compared their performance using a series of simulation and phantom validations. Results: Compared to the LUT approach, utilizing full TR, E and ⟨t⟩ datasets yield high-resolution OPs reconstruction results. Among the three datasets employed, full TR demonstrates the optimal accuracy. Conclusions: Utilizing the data obtained from SFD and TR measurement techniques allows for achieving high-resolution separation reconstruction of µa and µs' at different depths within 5 mm.