Ten Thousand Recaptures of a Single DNA Molecule in a Nanopore and Variance Reduction of Translocation Characteristics.

Nanopores have emerged as highly sensitive biosensors operating at the single-molecule level. However, the majority of nanopore experiments still rely on averaging signals from multiple molecules, introducing systematic errors. To overcome this limitation and obtain accurate information from a single molecule, the molecular ping-pong methodology provides a precise approach involving repeated captures of a single molecule. In this study, we have enhanced the molecular ping-pong technique by incorporating a customized electronic system and control algorithm, resulting in a recapture number exceeding 10,000. During the ping-pong process, we observed a significant reduction in the variance of translocation characteristics, providing fresh insights into single-molecule translocation dynamics. An inhomogeneous translocation velocity of folded DNA has been revealed, illustrating a strong interaction between the molecule and the solid-state nanopore. The results not only promise heightened experimental efficiency with reduced sample volume but also increase the precision in statistical analysis of translocation events, marking a significant stride toward authentic single-molecule nanopore sensing.

Physiological-Biochemical Characteristics and a Transcriptomic Profiling Analysis Reveal the Postharvest Wound Healing Mechanisms of Sweet Potatoes under Ascorbic Acid Treatment.

Sweet potatoes are extremely vulnerable to mechanical wounds during harvesting and postharvest handling. It is highly necessary to take measures to accelerate wound healing. The effect of 20 g L-1 of ascorbic acid (AA) treatment on the wound healing of sweet potatoes and its mechanisms were studied. The results validated that AA treatment significantly reduced the weight loss rate and disease index. AA treatment effectively enhanced the formation speed of lignin and SPP at the wound sites, decreased the MDA content, and maintained the cell membrane integrity. AA enhanced the activities of PAL, C4H, 4CL, CAD, and POD and increased the contents of chlorogenic acid, caffeic acid, sinapic acid, ferulic acid, cinnamic acid, p-coumaryl alcohol, sinapyl alcohol, coniferyl alcohol, and lignin. Based on a transcriptomic analysis, a total of 1200 genes were differentially expressed at the sweet potato wound sites by the AA treatment, among which 700 genes were upregulated and 500 genes were downregulated. The KEGG pathway analysis showed that the differentially expressed genes were mainly involved in phenylalanine, tyrosine, and tryptophan biosynthesis; phenylpropanoid biosynthesis; and other wound healing-related pathways. As verified by a qRT-PCR, the AA treatment significantly upregulated the gene expression levels of IbSKDH, IbADT/PDT, IbPAL, and Ib4CL at the wound sties.

Biochemical mechanism of chlorine dioxide fumigation in inhibiting Ceratocystis fimbriata and black rot in postharvest sweetpotato.

The inhibitory properties and underlying mechanism of chlorine dioxide (ClO2) fumigation on the pathogen Ceratocystis fimbriata (C. fimbriata) and resultant sweetpotato black rot were investigated in vitro and in vivo. Results revealed that the ClO2 fumigation effectively inhibited fungal growth and induced obvious morphological variation of C. fimbriata mycelia. Furthermore, the mycelial membrane suffered damage, as evidenced by a significant increase in malondialdehyde content and the leakage of protein and nucleic acid from mycelia cells, accompanied by a marked decrease in ergosterol content. Additionally, ClO2 fumigation caused spores cell membrane damage, a notable decrease in spore viability, and induced cell apoptosis as indicated by reductions in spore germination rate, two fluorescence staining observations, and flow cytometry analysis. Moreover, the decay diameter of sweetpotato black rot lesions decreased significantly after ClO2 fumigation, and the growth of C. fimbriata was also inhibited. These findings present a novel and effective technology for inhibiting the progression of sweetpotato black rot.

Microbiome-metabolomics-based insight into the protective effects of dietary fiber from sweetpotato residues on the high-fat diet-induced intestinal integrity damage.

Dietary fibers have attracted much attention due to their multiple benefits on gut health. In this work, the protective mechanism of dietary fiber from sweetpotato residues (SRDF) on the high-fat diet (HFD)-induced intestinal barrier injury was investigated using microbiome-metabolomics-based approach. The physicochemical property analysis demonstrated a thermal stability below 200 °C and porous pectin-polysaccharide structure of SRDF with high in vitro functional activities. The biochemical analysis indicated that SRDF significantly ameliorated intestinal barrier function by improving intestinal morphology and permeability and inhibiting inflammatory response. Microbiome analysis demonstrated that SRDF significantly reversed the HFD-induced dysbacteriosis, decreased the ratio of Firmicutes/Bacteroides and enhanced the relative abundance of probiotics, such as Muribaculaceae and Bifidobacteriaceae. Metabolomics analysis showed that SRDF also significantly altered the metabolic profile in the colon, wherein the differential metabolites were mainly involved in amino acid metabolism (especially tryptophan). Pearson correlation coefficient identified the beneficial relationship between intestinal microbiome and metabolome induced by SRDF. The limitation of this study was that the mouse model may not fully replicate the human intestinal responses due to the difference between the standard environmental conditions and natural world. Generally, our results implied the great potential of SRDF as a functional food ingredient.

Using large language model (LLM) to identify high-burden informal caregivers in long-term care.

BACKGROUND: The rising global elderly population increases the demand for caregiving, yet traditional methods may not fully assess the challenges faced by vital informal caregivers. OBJECTIVE: To investigate the efficacy of Large Language Model (LLM) in detecting overburdened informal caregivers, benchmarking against rule-based and machine learning methods. METHODS: 1,791 eligible informal caregivers from Southern Taiwan and utilized their textual case summary reports for the LLM. We also employed structured questionnaire results for machine learning models. Furthermore, we leveraged the visualization of the LLM's attention mechanisms to enhance our understanding of the model's interpretative capabilities. RESULTS: The LLM achieved an Area Under the Receiver Operating Characteristic (AUROC) curve of 0.84 and an Area Under the Precision-Recall Curve (AUPRC) of 0.70, marking an 8% and 14% improvement over traditional methods. The visualization of the attention mechanism accurately reflected the evaluations of human experts, concentrating on descriptions of high-burden descriptions and the relationships between caregivers and recipients. CONCLUSION: This research demonstrates the notable capability of LLM to accurately identify high-burden caregivers in Long-term Care (LTC) settings. Compared to traditional approaches, LLM offers an opportunity for the future of LTC research and policymaking.

Large negative differential conductance and its transformation in a single radical molecule.

The discovery of negative differential conductance (NDC) in a single molecule and mechanism controlling this phenomenon are important for molecular electronics. We investigated the electronic properties of a typical radical molecule 3-carbamoyl-2,2,5,5-tetramethyl-3-pyrrolin-1-yloxy (CTPO) on an Au(111) surface using low-temperature scanning tunneling microscopy (STM) and inelastic electron tunneling spectroscopy. Large NDC was observed in single CTPO molecules at the boundary of the crystal monolayer. The origin of observed NDC is revealed as the inelastic electron-phonon scattering during tunneling, and the strong spatial variation of the NDC over the single molecule illustrates the nature of the localized radical group. In addition, the NDC can be transformed into a positive differential conductance peak by tuning coupling strengths between different tunneling channels. An empirical multi-channel model has been developed to describe the competition between the valley-shaped NDC and peak-shaped positive differential conductance. The unique electronic property and giant conductance change observed in this radical molecule is valuable for designing novel molecular devices in the future.

High-precision high-speed nanopore ping-pong control system based on field programmable gate array.

"Molecular ping-pong," emerging as a control strategy in solid-state nanopore technology, presents a highly promising approach for repetitive measurements of single biomolecules, such as DNA. This paper introduces a high-precision, high-speed nanopore molecular ping-pong control system consisting of a home-built trans-impedance amplifier (TIA), a control system based on a Field Programmable Gate Array (FPGA), and a LabVIEW program operating on the host personal computer. Through feedback compensation and post-stage boosting, the TIA achieves a high bandwidth of about 200 kHz with a gain of 100 MΩ, along with low input-referred current noise of 1.6 × 10-4 pA2/Hz at 1 kHz and 1.1 × 10-3 pA2/Hz at 100 kHz. The FPGA-based control system demonstrates a minimum overall response time (tdelay) of 6.5 µs from the analog input current signal trigger to the subsequent reversal of the analog output drive voltage signal, with a control precision of 1 µs. Additionally, a LabVIEW program has been developed to facilitate rapid data exchange and communication with the FPGA program, enabling real-time signal monitoring, parameter adjustment, and data storage. Successful recapture of individual DNA molecules at various tdelay, resulting in an improvement in capture rate by up to 2 orders of magnitude, has been demonstrated. With unprecedented control precision and capture efficiency, this system provides robust technical support and opens novel research avenues for nanopore single-molecule sensing and manipulation.

Effect of Tea Tree Essential Oil on the Quality, Antioxidant Activity, and Microbiological Safety of Lightly Processed Lily (Lilium brownii var. viridulum) during Storage.

The Lanzhou lily is a regionally distinctive vegetable; the emergence of lightly processed lilies has addressed the inconvenience of consuming fresh lilies. However, the cleaning and impurity removal during the processing of lightly processed lily may strip off its original protective barrier and affect the edible quality. As one of the preservation methods, tea tree essential oil (TTEO) has the characteristics of being green, safe, and efficient preservative properties. This study focused on investigating the effects of different concentrations (25 µL/L, 50 µL/L, and 100 µL/L) of TTEO on the quality and microbiological safety of lightly processed lily. The results showed that compared with the control, appropriate concentrations of TTEO treatment could delay weight loss, improve appearance, firmness, and sensory quality, and maintain microbiological safety with the best effect observed at 50 µL/L. Meanwhile, TTEO treatment induced phenylalanine ammonia-lyase activity, thereby increasing the total phenolic content. Furthermore, TTEO enhanced the superoxide dismutase (SOD) and ascorbate peroxidase (APX) activity, which reduced O2-· production rate and H2O2 content. TTEO inhibited lipoxygenase (LOX) activity, reducing the relative conductivity and malondialdehyde content, thereby delaying lipid peroxidation and quality deterioration. This indicates that TTEO could enhance antioxidant capacity by regulating reactive oxygen species (ROS) metabolism and delay the quality deterioration of lightly processed lily by inhibiting lipid peroxidation.

Understanding and alleviating informal caregiver burden through the development and validation of a caregiver strain index-based model in Taiwan.

BACKGROUND: Quantifying the informal caregiver burden is important for understanding the risk factors associated with caregiver overload and for evaluating the effectiveness of services provided in Long-term Care (LTC). OBJECTIVE: This study aimed to develop and validate a Caregiver Strain Index (CSI)-based score for quantifying the informal caregiver burden, while the original dataset did not fully cover evaluation items commonly included in international assessments. Subsequently, we utilized the CSI-based score to pinpoint key caregiver burden risk factors, examine the initial timing of LTC services adoption, and assess the impact of LTC services on reducing caregiver burden. METHODS: The study analyzed over 28,000 LTC cases in Southern Taiwan from August 2019 to December 2022. Through multiple regression analysis, we identified significant risk factors associated with caregiver burden and examined changes in this burden after utilizing various services. Survival analysis was employed to explore the relationship between adopting the first LTC services and varying levels of caregiver burden. RESULTS: We identified 126 significant risk factors for caregiver burden. The most critical factors included caregiving for other disabled family members or children under the age of three (ß = 0.74, p < 0.001), the employment status of the caregiver (ß = 0.30-0.53, p < 0.001), the frailty of the care recipient (ß = 0.28-0.31, p < 0.001), and the behavioral symptoms of dementia in care recipients (ß = 0.28-2.60, p < 0.05). Generally, caregivers facing higher burdens sought LTC services earlier, and providing home care services alleviated the caregiver's burden. CONCLUSION: This comprehensive study suggests policy refinements to recognize high-risk caregivers better early and provide timely support to improve the overall well-being of both informal caregivers and care recipients.

FAK loss reduces BRAFV600E-induced ERK phosphorylation to promote intestinal stemness and cecal tumor formation.

BRAFV600E mutation is a driver mutation in the serrated pathway to colorectal cancers. BRAFV600E drives tumorigenesis through constitutive downstream extracellular signal-regulated kinase (ERK) activation, but high-intensity ERK activation can also trigger tumor suppression. Whether and how oncogenic ERK signaling can be intrinsically adjusted to a 'just-right' level optimal for tumorigenesis remains undetermined. In this study, we found that FAK (Focal adhesion kinase) expression was reduced in BRAFV600E-mutant adenomas/polyps in mice and patients. In Vil1-Cre;BRAFLSL-V600E/+;Ptk2fl/fl mice, Fak deletion maximized BRAFV600E's oncogenic activity and increased cecal tumor incidence to 100%. Mechanistically, our results showed that Fak loss, without jeopardizing BRAFV600E-induced ERK pathway transcriptional output, reduced EGFR (epidermal growth factor receptor)-dependent ERK phosphorylation. Reduction in ERK phosphorylation increased the level of Lgr4, promoting intestinal stemness and cecal tumor formation. Our findings show that a 'just-right' ERK signaling optimal for BRAFV600E-induced cecal tumor formation can be achieved via Fak loss-mediated downregulation of ERK phosphorylation.

Pharmacological suppression of the OTUD4/CD73 proteolytic axis revives antitumor immunity against immune-suppressive breast cancers.

Despite widespread utilization of immunotherapy, treating immune-cold tumors remains a challenge. Multiomic analyses and experimental validation identified the OTUD4/CD73 proteolytic axis as a promising target in treating immune-suppressive triple negative breast cancer (TNBC). Mechanistically, deubiquitylation of CD73 by OTUD4 counteracted its ubiquitylation by TRIM21, resulting in CD73 stabilization inhibiting tumor immune responses. We further demonstrated the importance of TGF-ß signaling for orchestrating the OTUD4/CD73 proteolytic axis within tumor cells. Spatial transcriptomics profiling discovered spatially resolved features of interacting malignant and immune cells pertaining to expression levels of OTUD4 and CD73. In addition, ST80, a newly developed inhibitor, specifically disrupted proteolytic interaction between CD73 and OTUD4, leading to reinvigoration of cytotoxic CD8+ T cell activities. In preclinical models of TNBC, ST80 treatment sensitized refractory tumors to anti-PD-L1 therapy. Collectively, our findings uncover what we believe to be a novel strategy for targeting the immunosuppressive OTUD4/CD73 proteolytic axis in treating immune-suppressive breast cancers with the inhibitor ST80.

Measuring the composition of the tumor microenvironment with transcriptome analysis: past, present and future.

Interactions between tumor cells and immune cells in the tumor microenvironment (TME) play a vital role the mechanisms of immune evasion, by which cancer cells escape immune elimination. Thus, the characterization and quantification of different components in the TME is a hot topic in molecular biology and drug discovery. Since the development of transcriptome sequencing in bulk tissue, single cells and spatial dimensions, there are increasing methods emerging to deconvolute and subtype the TME. This review discusses and compares such computational strategies and downstream subtyping analyses. Integrative analyses of the transcriptome with other data, such as epigenetics and T-cell receptor sequencing, are needed to obtain comprehensive knowledge of the dynamic TME.

[Box: see text].

Machine Learning Predicts Oxaliplatin Benefit in Early Colon Cancer.

PURPOSE: A combination of fluorouracil, leucovorin, and oxaliplatin (FOLFOX) is the standard for adjuvant therapy of resected early-stage colon cancer (CC). Oxaliplatin leads to lasting and disabling neurotoxicity. Reserving the regimen for patients who benefit from oxaliplatin would maximize efficacy and minimize unnecessary adverse side effects. METHODS: We trained a new machine learning model, referred to as the colon oxaliplatin signature (COLOXIS) model, for predicting response to oxaliplatin-containing regimens. We examined whether COLOXIS was predictive of oxaliplatin benefits in the CC adjuvant setting among 1,065 patients treated with 5-fluorouracil plus leucovorin (FULV; n = 421) or FULV + oxaliplatin (FOLFOX; n = 644) from NSABP C-07 and C-08 phase III trials. The COLOXIS model dichotomizes patients into COLOXIS+ (oxaliplatin responder) and COLOXIS- (nonresponder) groups. Eight-year recurrence-free survival was used to evaluate oxaliplatin benefits within each of the groups, and the predictive value of the COLOXIS model was assessed using the P value associated with the interaction term (int P) between the model prediction and the treatment effect. RESULTS: Among 1,065 patients, 526 were predicted as COLOXIS+ and 539 as COLOXIS-. The COLOXIS+ prediction was associated with prognosis for FULV-treated patients (hazard ratio [HR], 1.52 [95% CI, 1.07 to 2.15]; P = .017). The model was predictive of oxaliplatin benefits: COLOXIS+ patients benefited from oxaliplatin (HR, 0.65 [95% CI, 0.48 to 0.89]; P = .0065; int P = .03), but COLOXIS- patients did not (COLOXIS- HR, 1.08 [95% CI, 0.77 to 1.52]; P = .65). CONCLUSION: The COLOXIS model is predictive of oxaliplatin benefits in the CC adjuvant setting. The results provide evidence supporting a change in CC adjuvant therapy: reserve oxaliplatin only for COLOXIS+ patients, but further investigation is warranted.

Tea Polyphenols Inhibit the Occurrence of Enzymatic Browning in Fresh-Cut Potatoes by Regulating Phenylpropanoid and ROS Metabolism.

During fresh-cut processing, potatoes lose their inherent protective cellular structure, leading to enzymatic browning that compromises sensory and edible quality. Tea polyphenols (TPs), natural preservatives with potent reducing properties, are hypothesized to impact this browning process. However, their influence and regulatory mechanism on the enzymatic browning of fresh-cut potatoes remain poorly understood. This study used the "Holland Seven" potato as the research material to explore the effects of a treatment with different TP concentrations (0.1 g L-1, 0.2 g L-1, and 0.3 g L-1) on the browning phenomenon and quality of fresh-cut potatoes during storage. The results showed that appropriate concentrations of TP treatment had a good preservation effect on the appearance and edible quality of fresh-cut potatoes. Furthermore, exogenous TP treatment reduced the content of enzymatic browning substrates (caffeic acid, p-coumaric acid, and ferulic acid) by regulating phenylpropanoid metabolism. Meanwhile, TP treatment augmented the activities of antioxidative enzymes (superoxide dismutase, catalase, ascorbate peroxidase, and glutathione reductase), maintained higher levels of ascorbic acid (Vc), and reduced glutathione (GSH). Consequently, the TP treatment could inhibit enzymatic browning by regulating reactive oxygen species (ROS) metabolism and the Vc-GSH cycle in fresh-cut potatoes.

FAK loss reduces BRAFV600E-induced ERK phosphorylation to promote intestinal stemness and cecal tumor formation.

BRAF V600E mutation is a driver mutation in the serrated pathway to colorectal cancers. BRAFV600E drives tumorigenesis through constitutive downstream extracellular signal-regulated kinase (ERK) activation, but high-intensity ERK activation can also trigger tumor suppression. Whether and how oncogenic ERK signaling can be intrinsically adjusted to a "just-right" level optimal for tumorigenesis remains undetermined. In this study, we found that FAK (Focal adhesion kinase) expression was reduced in BRAFV600E-mutant adenomas/polyps in mice and patients. In Vill-Cre;BRAFV600E/+;Fakfl/fl mice, Fak deletion maximized BRAFV600E's oncogenic activity and increased cecal tumor incidence to 100%. Mechanistically, our results showed that Fak loss, without jeopardizing BRAFV600E-induced ERK pathway transcriptional output, reduced EGFR (epidermal growth factor receptor)-dependent ERK phosphorylation. Reduction in ERK phosphorylation increased the level of Lgr4, promoting intestinal stemness and cecal tumor formation. Our findings show that a "just-right" ERK signaling optimal for BRAFV600E-induced cecal tumor formation can be achieved via Fak loss-mediated downregulation of ERK phosphorylation.

An individualized Bayesian method for estimating genomic variants of hypertension.

BACKGROUND: Genomic variants of the disease are often discovered nowadays through population-based genome-wide association studies (GWAS). Identifying genomic variations potentially underlying a phenotype, such as hypertension, in an individual is important for designing personalized treatment; however, population-level models, such as GWAS, may not capture all the important, individualized factors well. In addition, GWAS typically requires a large sample size to detect the association of low-frequency genomic variants with sufficient power. Here, we report an individualized Bayesian inference (IBI) algorithm for estimating the genomic variants that influence complex traits, such as hypertension, at the level of an individual (e.g., a patient). By modeling at the level of the individual, IBI seeks to find genomic variants observed in the individual's genome that provide a strong explanation of the phenotype observed in this individual. RESULTS: We applied the IBI algorithm to the data from the Framingham Heart Study to explore the genomic influences of hypertension. Among the top-ranking variants identified by IBI and GWAS, there is a significant number of shared variants (intersection); the unique variants identified only by IBI tend to have relatively lower minor allele frequency than those identified by GWAS. In addition, IBI discovered more individualized and diverse variants that explain hypertension patients better than GWAS. Furthermore, IBI found several well-known low-frequency variants as well as genes related to blood pressure that GWAS missed in the same cohort. Finally, IBI identified top-ranked variants that predicted hypertension better than GWAS, according to the area under the ROC curve. CONCLUSIONS: The results support IBI as a promising approach for complementing GWAS, especially in detecting low-frequency genomic variants as well as learning personalized genomic variants of clinical traits and disease, such as the complex trait of hypertension, to help advance precision medicine.

[Comparison of posterolateral approach and combined approach in treatment of Mason type 2B posterior malleolar fracture].

Objective: To compare the effectiveness between the posterolateral approach and the posterolateral combined posteromedial approaches in the treatment of Mason type 2B posterior malleolar fracture. Methods: A retrospective analysis was performed on the clinical data of 79 patients with posterior ankle fracture who met the selection criteria between January 2015 and January 2022. There were 62 cases of Mason 2B Pilon subtype and 17 cases of avulsion subtype. Among Mason 2B Pilon subtype patients, 35 were treated with posterolateral approach (group A), 27 patients were treated with combined approach (group B). There was no significant difference in gender, age, injured side, cause of injury, time from injury to operation, preoperative hospital stay, preoperative visualanalogue scale (VAS) score, and intraoperative internal fixation between the two groups ( P>0.05). All patients with Mason 2B avulsion subtype were treated by posterolateral approach, including 7 males and 10 females, aged from 25 to 68 years, with an average of 46.1 years. The operation time, intraoperative blood loss, postoperative hospital stay, and complications were recorded. The reduction quality was evaluated by Ovadia deals radiographic score, and the ankle function and pain were evaluated by VAS score, American Orthopaedic Foot and Ankle Society (AOFAS) score, and ankle range of motion. Results: Mason 2B Pilon subtype: There was no significant difference in operation time, intraoperative blood loss, postoperative hospital stay, and follow-up time between the two groups ( P>0.05). The radiological evaluation of Ovadia deals in group A was significantly worse than that in group B ( P<0.05). The VAS score in the two groups significantly improved at each time point after operation, and the VAS score and AOFAS score further improved with the extension of time after operation, and the differences were significant ( P<0.05). Except that the AOFAS score of group A was significantly lower than that of group B at last follow-up ( P<0.05), there was no significant difference in VAS score and AOFAS score between the two groups at other time points ( P>0.05). At last follow-up, the ankle range of motion in group A was significantly less than that in group B ( P<0.05). There was no significant difference in the incidence of sural nerve injury, deep tissue infection, limitation of toe movement, and traumatic ankle arthritis between the two groups ( P>0.05). Mason 2B avulsion subtype: The operation time was (119.47±20.61) minutes and the intraoperative blood loss was 50 (35, 55) mL. Seventeen patients were followed up 13-25 months, with an average of 18 months. The Ovadia deals score was excellent in 10 cases, good in 6 cases, and poor in 1 case at 1 week after operation, and the excellent and good rate was 94.1%. All fractures healed in 8-18 weeks with an average of 12.35 weeks. There were 1 case of sural nerve injury and 3 cases of traumatic ankle arthritis after operation. No deep tissue infection or limitation of toe movement occurred. The VAS score decreased significantly and AOFAS score increased significantly with time, and the differences were significant between different time points before and after operation ( P<0.05). The ankle range of motion at last follow-up was (56.71±2.47)°. Conclusion: Compared with the posterolateral approach, the combined approach is a better choice for the treatment of Mason 2B Pilon subtype. If the posteromedial bone block does not affect the reduction of the medial malleolus, the posterolateral approach can achieve good effectiveness for Mason 2B avulsion subtype.

scGEM: Unveiling the Nested Tree-Structured Gene Co-Expressing Modules in Single Cell Transcriptome Data.

BACKGROUND: Single-cell transcriptome analysis has fundamentally changed biological research by allowing higher-resolution computational analysis of individual cells and subsets of cell types. However, few methods have met the need to recognize and quantify the underlying cellular programs that determine the specialization and differentiation of the cell types. METHODS: In this study, we present scGEM, a nested tree-structured nonparametric Bayesian model, to reveal the gene co-expression modules (GEMs) reflecting transcriptome processes in single cells. RESULTS: We show that scGEM can discover shared and specialized transcriptome signals across different cell types using peripheral blood mononuclear single cells and early brain development single cells. scGEM outperformed other methods in perplexity and topic coherence (p < 0.001) on our simulation data. Larger datasets, deeper trees and pre-trained models are shown to be positively associated with better scGEM performance. The GEMs obtained from triple-negative breast cancer single cells exhibited better correlations with lymphocyte infiltration (p = 0.009) and the cell cycle (p < 0.001) than other methods in additional validation on the bulk RNAseq dataset. CONCLUSIONS: Altogether, we demonstrate that scGEM can be used to model the hidden cellular functions of single cells, thereby unveiling the specialization and generalization of transcriptomic programs across different types of cells.

Predicting Long-Term Care Service Demands for Cancer Patients: A Machine Learning Approach.

BACKGROUND: Long-term care (LTC) service demands among cancer patients are significantly understudied, leading to gaps in healthcare resource allocation and policymaking. OBJECTIVE: This study aimed to predict LTC service demands for cancer patients and identify the crucial factors. METHODS: 3333 cases of cancers were included. We further developed two specialized prediction models: a Unified Prediction Model (UPM) and a Category-Specific Prediction Model (CSPM). The UPM offered generalized forecasts by treating all services as identical, while the CSPM built individual predictive models for each specific service type. Sensitivity analysis was also conducted to find optimal usage cutoff points for determining the usage and non-usage cases. RESULTS: Service usage differences in lung, liver, brain, and pancreatic cancers were significant. For the UPM, the top 20 performance model cutoff points were adopted, such as through Logistic Regression (LR), Quadratic Discriminant Analysis (QDA), and XGBoost (XGB), achieving an AUROC range of 0.707 to 0.728. The CSPM demonstrated performance with an AUROC ranging from 0.777 to 0.837 for the top five most frequently used services. The most critical predictive factors were the types of cancer, patients' age and female caregivers, and specific health needs. CONCLUSION: The results of our study provide valuable information for healthcare decisions, resource allocation optimization, and personalized long-term care usage for cancer patients.

Revealing the Impact of Genomic Alterations on Cancer Cell Signaling with an Interpretable Deep Learning Model.

Cancer is a disease of aberrant cellular signaling resulting from somatic genomic alterations (SGAs). Heterogeneous SGA events in tumors lead to tumor-specific signaling system aberrations. We interpret the cancer signaling system as a causal graphical model, where SGAs affect signaling proteins, propagate their effects through signal transduction, and ultimately change gene expression. To represent such a system, we developed a deep learning model called redundant-input neural network (RINN) with a transparent redundant-input architecture. Our findings demonstrate that by utilizing SGAs as inputs, the RINN can encode their impact on the signaling system and predict gene expression accurately when measured as the area under ROC curves. Moreover, the RINN can discover the shared functional impact (similar embeddings) of SGAs that perturb a common signaling pathway (e.g., PI3K, Nrf2, and TGF). Furthermore, the RINN exhibits the ability to discover known relationships in cellular signaling systems.