[Recent progress of chromatographic techniques for antibody purification].

Antibody drugs are becoming increasingly popular in disease diagnosis, targeted therapy, and immunoprevention owing to their characteristics of high targeting ability, strong specificity, low toxicity, and mild side effects. The demand for antibody drugs is steadily increasing, and their production scale is expanding. Upstream cell culture technology has been greatly improved by the high-capacity production of monoclonal antibodies. However, the downstream purification of antibodies presents a bottleneck in the production process. Moreover, the purification cost of antibodies is extremely high, accounting for approximately 50%-80% of the total cost of antibody production. Chromatographic technology, given its selectivity and high separation efficiency, is the main method for antibody purification. This process usually involves three stages: antibody capture, intermediate purification, and polishing. Different chromatographic techniques, such as affinity chromatography, ion-exchange chromatography, hydrophobic interaction chromatography, mixed-mode chromatography, and temperature-responsive chromatography, are used in each stage. Affinity chromatography, mainly protein A affinity chromatography, is applied for the selective capture and purification of antibodies from raw biofluids or harvested cell culture supernatants. Other chromatographic techniques, such as ion-exchange chromatography, hydrophobic interaction chromatography, and mixed-mode chromatography, are used for intermediate purification and antibody polishing. Affinity biomimetic chromatography and hydrophobic charge-induction chromatography can produce antibodies with purities comparable with those obtained through protein A chromatography, by employing artificial chemical/short peptide ligands with good selectivity, high stability, and low cost. Temperature-responsive chromatography is a promising technique for the separation and purification of antibodies. In this technique, antibody capture and elution is controlled by simply adjusting the column temperature, which greatly eliminates the risk of antibody aggregation and inactivation under acidic elution conditions. The combination of different chromatographic methods to improve separation selectivity and achieve effective elution under mild conditions is another useful strategy to enhance the yield and quality of antibodies. This review provides an overview of recent advances in the field of antibody purification using chromatography and discusses future developments in this technology.

Aerodynamic Simulation of Small Airway Resistance: A New Imaging Biomarker for Chronic Obstructive Pulmonary Disease.

Purpose: To develop a novel method for calculating small airway resistance using computational fluid dynamics (CFD) based on CT data and evaluate its value to identify COPD. Patients and Methods: 24 subjects who underwent chest CT scans and pulmonary function tests between August 2020 and December 2020 were enrolled retrospectively. Subjects were divided into three groups: normal (10), high-risk (6), and COPD (8). The airway from the trachea down to the sixth generation of bronchioles was reconstructed by a 3D slicer. The small airway resistance (RSA) and RSA as a percentage of total airway resistance (RSA%) were calculated by CFD combined with airway resistance and FEV1 measured by pulmonary function test. A correlation analysis was conducted between RSA and pulmonary function parameters, including FEV1/FVC, FEV1% predicted, MEF50% predicted, MEF75% predicted and MMEF75/25% predicted. Results: The RSA and RSA% were significantly different among the three groups (p<0.05) and related to FEV1/FVC (r = -0.70, p < 0.001; r = -0.67, p < 0.001), FEV1% predicted (r = -0.60, p = 0.002; r = -0.57, p = 0.004), MEF50% predicted (r = -0.64, p = 0.001; r = -0.64, p = 0.001), MEF75% predicted (r = -0.71, p < 0.001; r = -0.60, p = 0.002) and MMEF 75/25% predicted (r = -0.64, p = 0.001; r = -0.64, p = 0.001). Conclusion: Airway CFD is a valuable method for estimating the small airway resistance, where the derived RSA will aid in the early diagnosis of COPD.

Enhanced water stability and catalytic activity of Fe-based metal-organic frameworks with co-ligands for 2,4-dichlorophenol degradation.

Fe-based metal-organic frameworks (MOFs) have good photocatalytic performance, environmental friendliness, low cost, and abundance. However, their applications are limited by low water stability, particularly in the presence of light irradiation and oxidizing agents. In this study, we present a MIL-53(Fe)-based MOF using 1,4-naphthalene dicarboxylic (1,4-NDC) and 1,4-benzenedicarboxylic (H2BDC) acid co-ligands, denoted MIL-53(Fe)-Nx, where Nx represents the ratio of 1,4-NDC. This MOF exhibits high water stability and good photocatalytic activity because of the hydrophobicity of naphthalene. The removal and mineralization rates for 100 mg/L 2,4-dichlorophenol reached 100% and 22%, respectively, within 60 min. After three cycles of use, the Fe leached into the solution from the catalysts was significantly lower than the maximum permissible limit indicated in the European Union standard. Of note, 1,4-NDC can be used to make a rigid MOF, thereby improving the crystallinity, porosity, and hydrophobicity of the resultant materials. It also significantly reduced the bandgap energy and improved the charge separation efficiency of the catalysts. This study provides a route to enhance the water stability of Fe-based MOFs via a mixed-ligand strategy to expand their applications in pollutant control.

Heme-Mimetic Photosensitizer with Iron-Targeting and Internalizing Properties for Enhancing PDT Activity and Promoting Infected Diabetic Wound Healing.

The management of multibacterial infections remains clinically challenging in the care and treatment of chronic diabetic wounds. Photodynamic therapy (PDT) offers a promising approach to addressing bacterial infections. However, the limited target specificity and internalization properties of traditional photosensitizers (PSs) toward Gram-negative bacteria pose significant challenges to their antibacterial efficacy. In this study, we designed an iron heme-mimetic PS (MnO2@Fe-TCPP(Zn)) based on the iron dependence of bacteria that can be assimilated by bacteria and retained in different bacteria strains (Escherichia coli, Staphylococcus aureus, and methicillin-resistant Staphylococcus aureus) and which shows high PDT antibacterial efficacy. For accelerated wound healing after antibacterial treatment, MnO2@Fe-TCPP(Zn) was loaded into a zwitterionic hydrogel with biocompatibility and antifouling properties to form a nanocomposite antibacterial hydrogel (PSB-MnO2@Fe-TCPP(Zn)). In the multibacterial infectious diabetic mouse wound model, the PSB-MnO2@Fe-TCPP(Zn) hydrogel dressing rapidly promoted skin regeneration by effectively inhibiting bacterial infections, eliminating inflammation, and promoting angiogenesis. This study provides an avenue for developing broad-spectrum antibacterial nanomaterials for combating the antibiotic resistance crisis and promoting the healing of complex bacterially infected wounds.

A facile and intelligent detection method for diclazuril based on a stable dual emissive Eu3+-dopped metal-organic framework.

Diclazuril (DIC) is a broad-spectrum anti-coccidiosis drug of the triazine class, widely used in poultry farming. The overuse of DIC may lead to its accumulation in animal bodies, which may enter the food chain and threaten human health. In this work, we fabricated a stable Eu3+-doped UiO-66 fluorescence sensor (EuUHIPA-30) for the sensitive detection of DIC. Among 20 veterinary drugs, the fluorescence of EuUHIPA-30 selectively responds to DIC, with a low detection limit (0.19 µM) and fast response (10 s). EuUHIPA-30 is recyclable and can detect DIC in chicken and eggs with good recoveries. Moreover, a smartphone-integrated paper-based sensor enables the instrument-free, rapid, visual, and intelligent detection of DIC in chickens and eggs. This work provides a promising candidate for practical fluorescent DIC sensing in animal-derived food to promote food safety.

CircHIRA sponges miR-196b-5p to promote porcine early embryonic development.

Circular RNA (circRNA) is abundantly expressed in preimplantation embryos and embryonic stem cells in mice and humans. However, its function and mechanism in early development of mammalian embryos remain unclear. Here, we showed that circHIRA mediated miR-196b-5p to regulate porcine early embryonic development. We verified the circular feature of circHIRA by sanger sequencing, and proved the authenticity of circHIRA by enzyme digestion test. HIRA and circHIRA were expressed in porcine early embryos, and its expression levels significantly increased from 8-cell stage onwards and reached the maximum at the blastocyst stage. Functional studies revealed that circHIRA knockdown not only significantly reduced the developmental efficiency of embryos from 8-cell stage to blastocyst stage, but also impaired the blastocyst quality. Mechanistically, integrated analysis of miRNA prediction and gene expression showed that circHIRA knockdown significantly increased the expression of miR-196b-5p in porcine early embryos. Furthermore, miR-196b-5p inhibitor injection could rescue the early development of circHIRA knockdown embryos. Taken together, the findings reveal that circHIRA regulates porcine early embryonic development via inhibiting the expression of miR-196b-5p.

A Serial Multi-Scale Feature Fusion and Enhancement Network for Amur Tiger Re-Identification.

The Amur tiger is an important endangered species in the world, and its re-identification (re-ID) plays an important role in regional biodiversity assessment and wildlife resource statistics. This paper focuses on the task of Amur tiger re-ID based on visible light images from screenshots of surveillance videos or camera traps, aiming to solve the problem of low accuracy caused by camera perspective, noisy background noise, changes in motion posture, and deformation of Amur tiger body patterns during the re-ID process. To overcome this challenge, we propose a serial multi-scale feature fusion and enhancement re-ID network of Amur tiger for this task, in which global and local branches are constructed. Specifically, we design a global inverted pyramid multi-scale feature fusion method in the global branch to effectively fuse multi-scale global features and achieve high-level, fine-grained, and deep semantic feature preservation. We also design a local dual-domain attention feature enhancement method in the local branch, further enhancing local feature extraction and fusion by dividing local feature blocks. Based on the above model structure, we evaluated the effectiveness and feasibility of the model on the public dataset of the Amur Tiger Re-identification in the Wild (ATRW), and achieved good results on mAP, Rank-1, and Rank-5, demonstrating a certain competitiveness. In addition, since our proposed model does not require the introduction of additional expensive annotation information and does not incorporate other pre-training modules, it has important advantages such as strong transferability and simple training.

Sex differences in anhedonia in bipolar depression: a resting-state fMRI study.

Previous studies about anhedonia symptoms in bipolar depression (BD) ignored the unique role of gender on brain function. This study aims to explore the regional brain neuroimaging features of BD with anhedonia and the sex differences in these patients. The resting-fMRI by applying fractional amplitude of low-frequency fluctuation (fALFF) method was estimated in 263 patients with BD (174 high anhedonia [HA], 89 low anhedonia [LA]) and 213 healthy controls. The effects of two different factors in patients with BD were analyzed using a 3 (group: HA, LA, HC) × 2 (sex: male, female) ANOVA. The fALFF values were higher in the HA group than in the LA group in the right medial cingulate gyrus and supplementary motor area. For the sex-by-group interaction, the fALFF values of the right hippocampus, left medial occipital gyrus, right insula, and bilateral medial cingulate gyrus were significantly higher in HA males than in LA males but not females. These results suggested that the pattern of high activation could be a marker of anhedonia symptoms in BD males, and the sex differences should be considered in future studies of BD with anhedonia symptoms.

Self-distillation framework for document-level relation extraction in low-resource environments.

The objective of document-level relation extraction is to retrieve the relations existing between entities within a document. Currently, deep learning methods have demonstrated superior performance in document-level relation extraction tasks. However, to enhance the model's performance, various methods directly introduce additional modules into the backbone model, which often increases the number of parameters in the overall model. Consequently, deploying these deep models in resource-limited environments presents a challenge. In this article, we introduce a self-distillation framework for document-level relational extraction. We partition the document-level relation extraction model into two distinct modules, namely, the entity embedding representation module and the entity pair embedding representation module. Subsequently, we apply separate distillation techniques to each module to reduce the model's size. In order to evaluate the proposed framework's performance, two benchmark datasets for document-level relation extraction, namely GDA and DocRED are used in this study. The results demonstrate that our model effectively enhances performance and significantly reduces the model's size.

A Pilot Study on a Possible Mechanism behind Olfactory Dysfunction in Parkinson's Disease: The Association of TAAR1 Downregulation with Neuronal Loss and Inflammation along Olfactory Pathway.

Parkinson's disease (PD) is characterized not only by motor symptoms but also by non-motor dysfunctions, such as olfactory impairment; the cause is not fully understood. Our study suggests that neuronal loss and inflammation in brain regions along the olfactory pathway, such as the olfactory bulb (OB) and the piriform cortex (PC), may contribute to olfactory dysfunction in PD mice, which might be related to the downregulation of the trace amine-associated receptor 1 (TAAR1) in these areas. In the striatum, although only a decrease in mRNA level, but not in protein level, of TAAR1 was detected, bioinformatic analyses substantiated its correlation with PD. Moreover, we discovered that neuronal death and inflammation in the OB and the PC in PD mice might be regulated by TAAR through the Bcl-2/caspase3 pathway. This manifested as a decrease of anti-apoptotic protein Bcl-2 and an increase of the pro-apoptotic protein cleaved caspase3, or through regulating astrocytes activity, manifested as the increase of TAAR1 in astrocytes, which might lead to the decreased clearance of glutamate and consequent neurotoxicity. In summary, we have identified a possible mechanism to elucidate the olfactory dysfunction in PD, positing neuronal damage and inflammation due to apoptosis and astrocyte activity along the olfactory pathway in conjunction with the downregulation of TAAR1.

Electron-Phonon Interaction Mediated Gigantic Enhancement of Thermoelectric Power Factor Induced by Topological Phase Transition.

We propose an effective strategy to significantly enhance the thermoelectric power factor (PF) of a series of 2D semimetals and semiconductors by driving them toward a topological phase transition (TPT). Employing first-principles calculations with an explicit consideration of electron-phonon interactions, we analyze the electronic transport properties of germanene across the TPT by applying hydrogenation and biaxial strain. We reveal that the nontrivial semimetal phase, hydrogenated germanene with 8% biaxial strain, achieves a considerable 4-fold PF enhancement, attributed to the highly asymmetric electronic structure and semimetallic nature of the nontrivial phase. We extend the strategy to another two representative 2D materials (stanene and HgSe) and observe a similar trend, with a marked 7-fold and 5-fold increase in PF, respectively. The wide selection of functional groups, universal applicability of biaxial strain, and broad spectrum of 2D semimetals and semiconductors render our approach highly promising for designing novel 2D materials with superior thermoelectric performance.

Hypoxia-induced TRPM7 promotes glycolytic metabolism and progression in hepatocellular carcinoma.

BACKGROUND: Hypoxia disrupts glucose metabolism in hepatocellular carcinoma (HCC). Transient receptor potential cation channel, subfamily M, member 7 (TRPM7) plays an ontogenetic role. Thus, we aimed to explore the regulation of TRPM7 by hypoxia-induced factor (HIF) and its underlying mechanisms in HCC. METHODS: hypoxia was induced in multiple HCC cells using 1% O2 or CoCl2 treatment, and subsequently blocked using siRNAs targeting HIF-1α or HIF-2α as well as a HIF-1α protein synthesis inhibitor. The levels of HIF-1α and TRPM7 were assessed using quantitative PCR (qPCR) and Western blot analysis. Chromatin immunoprecipitation (ChIP) and luciferase assays were performed to observe the regulation of TRPM7 promoter regions by HIF-1α. A PCR array was utilized to screen glucose metabolism-related enzymes in HEK293 cells overexpressing TRPM7 induced by tetracycline, and then verified in TRPM7-overexpressed huh7 cells. Finally, CCK-8, transwell, scratch and tumor formation experiments in nude mice were conducted to examine the effect of TRPM7 on proliferation and metastasis in HCC. RESULTS: Exposure to hypoxia led to increase the levels of TRPM7 and HIF-1α in HCC cells, which were inhibited by HIF-1α siRNA or enhanced by HIF-1α overexpression. HIF-1α directly bound to two hypoxia response elements (HREs) in the TRPM7 promoter. Several glycolytic metabolism-related enzymes, were simultaneously upregulated in HEK293 and huh7 cells overexpressing TRPM7 during hypoxia. In vitro and in vivo experiments demonstrated that TRPM7 promoted the proliferation and metastasis of HCC cells. CONCLUSIONS: TRPM7 was directly transcriptionally regulated by HIF-1α, leading to glycolytic metabolic reprogramming and the promotion of HCC proliferation and metastasis in vitro and in vivo. Our findings suggest that TRPM7 might be a potential diagnostic indicator and therapeutic target for HCC.

MPRAVarDB: an online database and web server for exploring regulatory effects of genetic variants.

Massively parallel reporter assay (MPRA) is an important technology to evaluate the impact of genetic variants on gene regulation. Here, we present MPRAVarDB, an online database and web server, for exploring regulatory effects of genetic variants. MPRAVarDB harbors 18 MPRA experiments designed to assess the regulatory effects of genetic variants associated with GWAS loci, eQTLs and various genomic features, resulting in a total of 242,818 variants tested across more than 30 cell lines and 30 human diseases or traits. MPRAVarDB empowers the query of MPRA variants by genomic region, disease and cell line or by any combination of these query terms. Notably, MPRAVarDB offers a suite of pretrained machine learning models tailored to the specific disease and cell line, facilitating the genome-wide prediction of regulatory variants. MPRAVarDB is friendly to use, and users only need a few clicks to receive query and prediction results.

Comparison of deep-learning and radiomics-based machine-learning methods for the identification of chronic obstructive pulmonary disease on low-dose computed tomography images.

Background: Radiomics and artificial intelligence approaches have been developed to predict chronic obstructive pulmonary disease (COPD), but it is still unclear which approach has the best performance. Therefore, we established five prediction models that employed deep-learning (DL) and radiomics-based machine-learning (ML) approaches to identify COPD on low-dose computed tomography (LDCT) images and compared the relative performance of the different models to find the best model for identifying COPD. Methods: This retrospective analysis included 1,024 subjects (169 COPD patients and 855 control subjects) who underwent LDCT scans from August 2018 to July 2021. Five prediction models, including models that employed computed tomography (CT)-based radiomics features, chest CT images, quantitative lung density parameters, and demographic and clinical characteristics, were established to identify COPD by DL or ML approaches. Model 1 used CT-based radiomics features by ML method. Model 2 used a combination of CT-based radiomics features, lung density parameters, and demographic and clinical characteristics by ML method. Model 3 used CT images only by DL method. Model 4 used a combination of CT images, lung density parameters, and demographic and clinical characteristics by DL method. Model 5 used a combination of CT images, CT-based radiomics features, lung density parameters, and demographic and clinical characteristics by DL method. The accuracy, sensitivity, specificity, highest negative predictive values (NPVs), positive predictive values, and areas under the receiver operating characteristic (AUC) curve of the five prediction models were compared to examine their performance. The DeLong test was used to compare the AUCs of the different models. Results: In total, 107 radiomics features were extracted from each subject's CT images, 17 lung density parameters were acquired by quantitative measurement, and 18 selected demographic and clinical characteristics were recorded in this study. Model 2 had the highest AUC [0.73, 95% confidence interval (CI): 0.64-0.82], while model 3 had the lowest AUC (0.65, 95% CI: 0.55-0.75) in the test set. Model 2 also had the highest sensitivity (0.84), the highest accuracy (0.81), and the highest NPV (0.36). In the test set, based on the AUC results, Model 2 significantly outperformed Model 1 (P=0.03). Conclusions: The results showed that the identification ability of models that employ CT-based radiomics features combined with lung density parameters, and demographic and clinical characteristics using ML methods performed better than the chest CT image-based DL methods. ML methods are more suitable and beneficial for COPD identification.

Chemical Synthesis of a Branched Nonasaccharide Fragment from Helicobacter pylori Lipopolysaccharide.

A chemical synthesis of a unique nanosaccharide fragment from Helicobacter pylori lipopolysaccharide was achieved via a convergent glycosylation method. Challenges involved in the synthesis include the highly stereoselective construction of ß-3-deoxy-d-manno-oct-2-ulosonic acid (Kdo) and two 1,2-cis-glycosidic linkages, as well as the formation of a branched 2,7-disubstituted heptose subunit. Hydrogen-bond mediated aglycone delivery strategy and benzoyl-directing remote participation effect were employed, respectively, for the efficient generation of the desired ß-Kdo glycoside and 1,2-cis-α-l-fucoside/d-glucoside. Moreover, the key branched framework was successfully established through a [(7 + 1) + 1] assembly approach involving the stepwise glycosylation of the heptasaccharide alcohol with two monosaccharide donors. The synthesized 1 containing a propylamine linker at the reducing end can be covalently bound to a carrier protein for further immunological studies.

First-line sintilimab with pegaspargase, gemcitabine, and oxaliplatin in advanced extranodal natural killer/T cell lymphoma (SPIRIT): a multicentre, single-arm, phase 2 trial.

BACKGROUND: Programmed cell death protein 1 (PD-1) inhibitor sintilimab is effective in relapsed and refractory extranodal natural killer/T cell lymphoma (ENKTL), nasal type. We aimed to assess the safety and activity of sintilimab plus P-GEMOX (pegaspargase, gemcitabine, and oxaliplatin) in the first-line setting for advanced ENKTL. METHODS: The multicentre, single-arm, phase 2 trial was done at three medical centres in China. Patients aged 18-75 years with treatment-naive pathologically confirmed advanced ENKTL and an with Eastern Cooperative Oncology Group performance status score of 0-2 were eligible. Patients received intravenous sintilimab (200 mg on day 1), intramuscular pegaspargase (2000 U/m2 on day 1), intravenous gemcitabine (1 g/m2 on days 1 and 8), and intravenous oxaliplatin (130 mg/m2 on day 1) every 3 weeks for six cycles, followed by intravenous sintilimab (200 mg) every 3 weeks for up to 2 years or until disease progression or unacceptable toxicities. The primary endpoint was the complete response rate in the intention-to-treat population. The secondary endpoints were overall response rate (ORR), progression-free survival (PFS), disease-free survival (DFS), and overall survival. This trial is registered with ClinicalTrials.gov, NCT04127227. Enrolment has been completed, and follow-up is ongoing. FINDINGS: Between Nov 29, 2019, and Sept 7, 2022, 34 eligible patients were enrolled (median age 39 years [IQR 32-55]; 25 [74%] of 34 patients were male; nine [26%] were female; and all were of Asian ethnicity). At the data cutoff (July 20, 2023), the median follow-up was 21 months (IQR 13-32). The complete response rate was 85% (29 of 34 patients, 95% CI 70-94). Five patients (15%; 95% CI 7-30) attained partial response and the ORR was 100% (34 of 34 patients). 24-month PFS was 64% (95% CI 48-86), 24-month DFS was 72% (54-95), and 36-month overall survival was 76% (52-100). The most common grade 3 or 4 treatment-related adverse events were neutropenia (17 [50%] of 34 patients), anaemia (10 [29%] patients), and hypertriglyceridemia (10 [29%] patients). Hypothyroidism was the most frequent immune-related adverse event (18 [53%]), including grade 3 hypothyroidism in one (3%) patient that caused treatment termination. No severe adverse events occurred. There were three deaths: one due to haemophagocytic syndrome, one due to disease progression, and one due to unknown cause, which were not considered to be treatment related. INTERPRETATION: Combination of sintilimab with P-GEMOX seems to be an active and safe first-line regimen for patients with advanced ENKTL. FUNDING: National Key Research and Development Program and National Natural Science Foundation of China, Guangzhou Science and Technology Program and the Clinical Oncology Foundation of Chinese Society of Clinical Oncology.

HFpEF as systemic disease, insight from a diagnostic prediction model reminiscent of systemic inflammation and organ interaction in HFpEF patients.

Systemic inflammation and reciprocal organ interactions are associated with the pathophysiology of heart failure with preserved ejection fraction (HFpEF). However, the clinical value, especially the diagnositc prediction power of inflammation and extra-cardiac organ dysfunction for HfpEF is not explored. In this cross-sectional study, 1808 hospitalized patients from January 2014 to June 2022 in ChiHFpEF cohort were totally enrolled according to inclusion and exclusion criteria. A diagnostic model with markers from routine blood test as well as liver and renal dysfunction for HFpEF was developed using data from ChiHFpEF-cohort by logistic regression and assessed by receiver operating characteristic curve (ROC) and Brier score. Then, the model was validated by the tenfold cross-validation and presented as nomogram and a web-based online risk calculator as well. Multivariate and LASSO regression analysis revealed that age, hemoglobin, neutrophil to lymphocyte ratio, AST/ALT ratio, creatinine, uric acid, atrial fibrillation, and pulmonary hypertension were associated with HFpEF. The predictive model exhibited reasonably accurate discrimination (ROC, 0.753, 95% CI 0.732-0.772) and calibration (Brier score was 0.200). Subsequent internal validation showed good discrimination and calibration (AUC = 0.750, Brier score was 0.202). In additoin to participating in pathophysiology of HFpEF, inflammation and multi-organ interactions have diagnostic prediction value for HFpEF. Screening and optimizing biomarkers of inflammation and multi-organ interactions stand for a new field to improve noninvasive diagnostic tool for HFpEF.

Proteomic predictors of individualized nutrient-specific insulin secretion in health and disease.

Population level variation and molecular mechanisms behind insulin secretion in response to carbohydrate, protein, and fat remain uncharacterized despite ramifications for personalized nutrition. Here, we define prototypical insulin secretion dynamics in response to the three macronutrients in islets from 140 cadaveric donors, including those diagnosed with type 2 diabetes. While islets from the majority of donors exhibited the expected relative response magnitudes, with glucose being highest, amino acid moderate, and fatty acid small, 9% of islets stimulated with amino acid and 8% of islets stimulated with fatty acids had larger responses compared with high glucose. We leveraged this insulin response heterogeneity and used transcriptomics and proteomics to identify molecular correlates of specific nutrient responsiveness, as well as those proteins and mRNAs altered in type 2 diabetes. We also examine nutrient-responsiveness in stem cell-derived islet clusters and observe that they have dysregulated fuel sensitivity, which is a hallmark of functionally immature cells. Our study now represents the first comparison of dynamic responses to nutrients and multi-omics analysis in human insulin secreting cells. Responses of different people's islets to carbohydrate, protein, and fat lay the groundwork for personalized nutrition. ONE-SENTENCE SUMMARY: Deep phenotyping and multi-omics reveal individualized nutrient-specific insulin secretion propensity.

Demographic and Clinical Factors Associated With Health-Related Quality-of-Life Profiles Among Prostate Cancer Survivors.

PURPOSE: Our purpose was to describe the prevalence and predictors of symptom and function clusters related to physical, emotional, and social components of general health-related quality of life (HRQOL) in a population-based sample of prostate cancer (PCa) survivors. METHODS: Participants (N = 1,162) completed a baseline survey at a median of 9 months after diagnosis to ascertain the co-occurrence of eight symptom and functional domains that are common across all cancers and not treatment-specific. We used latent profile analysis (LPA) to identify subgroup profiles of survivors with low, moderate, or high HRQOL levels. Multinomial logistic regression models were used to identify clinical and sociodemographic factors associated with survivors' membership in the low versus moderate or high HRQOL profile. RESULTS: The LPA identified 16% of survivors who were categorized in the low HRQOL profile at baseline, indicative of the highest symptom burden and lowest functioning. Factors related to survivors' membership in the low versus higher HRQOL profile groups included less than age 65 years at diagnosis, identifying as non-Hispanic Black race, not working, being a former versus never smoker, systemic therapy, less companionship, more comorbidities, lower health care financial well-being, or less spirituality. Several factors remained associated with remaining in the low versus higher HRQOL profiles on the follow-up survey (n = 699), including younger age, Black race, comorbidity, and lower financial and spiritual well-being. CONCLUSION: About one of six PCa survivors experienced elevated physical and psychosocial symptoms that were independent of local curative therapy, but with younger age, race, comorbidity, and lower financial and spiritual well-being as stable risk factors for poor HRQOL over time.