Rapid and sensitive detection of Staphylococcus aureus using a THz metamaterial biosensor based on aptamer-functionalized Fe3O4@Au nanocomposites

Staphylococcus aureus (S. aureus) poses a serious threat to global public health, necessitating the establishment of rapid and simple tools for its accurate identification. Herein, we developed a terahertz (THz) metamaterial biosensor based on aptamer-functionalized Fe3O4@Au nanocomposites for quantitative S. aureus assays in different clinical samples. Fe3O4@Au@Cys@Apt has the dual advantages of magnetism and a high refractive index in the THz range and was used to rapidly separate and enrich target bacteria in a complex environmental solution. Furthermore, conjugation to the nanocomposites significantly increased the resonance frequency shift of the THz metamaterial after target loading. Our results showed that the shifts in the metamaterial resonance frequency were linearly related to S. aureus concentrations ranging from 1.0 × 103 to 1.0 × 107 CFU/mL, with a detection limit of 4.78 × 102 CFU/mL. The biosensor was further applied to S. aureus detection in spiked human urine and blood with satisfactory recoveries (82.4-109.6%). Our approach also demonstrated strong concordance with traditional plate counting (R2 = 0.99306) while significantly lowering the analysis time from 24 h to <1 h. In conclusion, the proposed biosensor can not only perform culture-free and extraction-free detection of target bacteria but can also be easily extended to the determination of other pathogenic bacteria, rendering it suitable for various bacteria-related disease diagnoses.

Hot spots and trends in microbial disease research on cultural heritage: a bibliometric analysis

This study is to understand and analyze the development history, research hotspots, and research trends in the study of microbial diseases of cultural heritage through bibliometric analyses in order to fill the current gap of no literature review in this research field and to make certain contributions to the research in this field and the protection of cultural heritage. Bibliometric and visual analyses of the literature on cultural heritage microbial diseases in the Web of Science (WoS) core collection were carried out using VOSviewer and R-bibliometrix, choosing the two main literature types of papers and reviews. The emphasis was placed on analyzing and summarizing core research strengths, hotspots, and trends. Six hundred sixty-seven documents (573 articles and 94 reviews) were retrieved. αIn the WoS core collection, the first literature on cultural heritage microbial disease research was published in January 2000, and the annual number of publications from 2000 to 2009 did not exceed one; the annual number of publications from 2010 onwards increased rapidly, and after 2018, the number of publications per year exceeded 60, reaching 94 in 2020, which indicates that cultural heritage microbial disease research is booming. Our research showed that Italy, the USA, and China were the leading research countries, and Univ Milan was the institution with the most publications. International Biodeterioration &Biodegradation was the most published and co-cited journal, and Gu JD was the most prolific author. The research hotspots in the study of microbial diseases of cultural heritage mainly include biological degradation of cultural heritage; identification of diseased microorganisms and disease mechanisms; cultural heritage microbial disease prevention and control methods; monitoring, prevention, and control of diseased microorganisms in indoor air; antibacterial agents, especially essential oils, nanoparticles, and other safe and efficient antibacterial products research and development; and exploration of the mechanisms of biofilm protection of cultural heritage on cultural heritage surfaces. Monitoring and identifying cultural heritage microbial communities, identifying disease mechanisms, and researching safe and efficient bacteriostatic products such as essential oils and nanoparticles will be the main research directions in the field of cultural heritage microbial disease prevention and control in the future.

Synoptic Reporting by Summarizing Cancer Pathology Reports using Large Language Models

Background

Synoptic reporting, the documenting of clinical information in a structured manner, is known to improve patient care by reducing errors, increasing readability, interoperability, and report completeness. Despite its advantages, manually synthesizing synoptic reports from narrative reports is expensive and error prone when the number of structured fields are many. While the recent revolutionary developments in Large Language Models (LLMs) have significantly advanced natural language processing, their potential for innovations in medicine is yet to be fully evaluated.

Objectives

In this study, we explore the strengths and challenges of utilizing the state-of-the-art language models in the automatic synthesis of synoptic reports.

Materials and Methods

We use a corpus of 7,774 cancer related, narrative pathology reports, which have annotated reference synoptic reports from Mayo Clinic EHR. Using these annotations as a reference, we reconfigure the state-of-the-art large language models, such as LLAMA-2, to generate the synoptic reports. Our annotated reference synoptic reports contain 22 unique data elements. To evaluate the accuracy of the reports generated by the LLMs, we use several metrics including the BERT F1 Score and verify our results by manual validation.

Results

We show that using fine-tuned LLAMA-2 models, we can obtain BERT Score F1 of 0.86 or higher across all data elements and BERT F1 scores of 0.94 or higher on over 50% (11 of 22) of the questions. The BERT F1 scores translate to average accuracies of 76% and as high as 81% for short clinical reports.

Conclusions

We demonstrate successful automatic synoptic report generation by fine-tuning large language models.

Discovery of novel amide derivatives as potent quorum sensing inhibitors of Pseudomonas aeruginosa

With the increasing reports of antibiotic resistance in this species, Pseudomonas aeruginosa is a common human pathogen with important implications for public health. Bacterial quorum sensing (QS) systems are potentially broad and versatile targets for developing new antimicrobial compounds. While previous reports have demonstrated that certain amide compounds can inhibit bacterial growth, there are few reports on the specific inhibitory effects of these compounds on bacterial quorum sensing systems. In this study, thirty-one amide derivatives were synthesized. The results of the biological activity assessment indicated that A9 and B6 could significantly inhibit the expression of lasB, rhlA, and pqsA, effectively reducing several virulence factors regulated by the QS systems of PAO1. Additionally, compound A9 attenuated the pathogenicity of PAO1 to Galleria mellonella larvae. Meanwhile, RT-qPCR, SPR, and molecular docking studies were conducted to explore the mechanism of these compounds, which suggests that compound A9 inhibited the QS systems by binding with LasR and PqsR, especially PqsR. In conclusion, amide derivatives A9 and B6 exhibit promising potential for further development as novel QS inhibitors in P. aeruginosa.

Best acupuncture method for mammary gland hyperplasia: Evaluation of randomized controlled trials and Bayesian network meta-analysis

Objective

To evaluate the effectiveness of different acupuncture treatments for mammary gland hyperplasia (MGH) using a network meta-analysis.

Methods

Several databases were searched without language restrictions from 2000 to February 2023, including PubMed, Embase, Web of Science, Cochrane Library, China Science and Technology Journal Database, China Biology Medicine Database, Wanfang Database, China National Knowledge Infrastructure Database, and other professional websites and gray literature. Inclusion criteria were adult women diagnosed with MGH; intervention measures included acupuncture and related therapies; the control group was treated with simple drugs; and the research type was a randomized controlled trial (RCT). The primary outcomes were treatment effectiveness and estradiol and progesterone levels. Secondary outcomes were breast lump size and visual analog scale (VAS) score of breast pain. Exclusion criteria were studies unrelated to MGH, incorrect study populations, control measures or interventions, incomplete data, non-RCTs, case reports, and animal experiments. Cochrane tools were used to assess the risk of bias. The R software (x64 version 4.2.1), Review Manager 5.3 software and STATA 16.0 software were used for data analysis.

Results

Following a rigorous screening process, data extraction, and quality assessment, 48 eligible RCTs encompassing 4,500 patients with MGH and 16 interventions were included. The results indicated that acupuncture, alone or in combination with traditional Chinese or Western medicine, had better therapeutic effects than conventional therapy. In terms of effectiveness, warm needle acupuncture was the best choice (94.6%). Bloodletting pricking was the most effective method (85.7%) for lowering progesterone levels. Bloodletting pricking was the most effective method (98.3%) for lowering estradiol levels. Manual acupuncture combined with traditional Chinese medicine was the most effective (74.5%) treatment to improve the size of the breast lump. Warm needle acupuncture was the most effective (69.8%) in improving the VAS score.

Conclusion

Acupuncture therapy was more effective in treating MGH than drug therapy alone, and warm needle acupuncture and bloodletting pricking were the two best options. However, larger sample sizes and high-quality RCTs are required.

Age-related trajectories of the development of social cognition

Age-related trajectories of intrinsic functional connectivity (iFC), which represent the interconnections between discrete regions of the human brain, for processes related to social cognition (SC) provide evidence for social development through neural imaging and can guide clinical interventions when such development is atypical. However, due to the lack of studies investigating brain development over a wide range of ages, the neural mechanisms of SC remain poorly understood, although considerable behavior-related evidence is available. The present study mapped vortex-wise iFC features between SC networks and the entire cerebral cortex by using common functional networks, creating the corresponding age-related trajectories. Three networks [moral cognition, theory of mind (ToM), and empathy] were selected as representative SC networks. The Enhanced Nathan Kline Institute-Rockland Sample (NKI-RS, N = 316, ages 8-83 years old) was employed delineate iFC characteristics and construct trajectories. The results showed that the SC networks display unique and overlapping iFC profiles. The iFC of the empathy network, an age-sensitive network, with dorsal attention network was found to exhibit a linear increasing pattern, that of the ventral attention network was observed to exhibit a linear decreasing pattern, and that of the somatomotor and dorsal attention networks was noted to exhibit a quadric-concave iFC pattern. Additionally, a sex-specific effect was observed for the empathy network as it exhibits linear and quadric sex-based differences in iFC with the frontoparietal and vision networks, respectively. The iFC of the ToM network with the ventral attention network exhibits a pronounced quadric-convex (inverted U-shape) trajectory. No linear or quadratic trajectories were noted in the iFC of the moral cognition network. These findings indicate that SC networks exhibit iFC with both low-level (somatomotor, vision) and high-level (attention and control) networks along specific developmental trajectories. The age-related trajectories determined in this study advance our understanding of the neural mechanisms of SC, providing valuable references for identification and intervention in cases of development of atypical SC.

Quality of Answers of Generative Large Language Models Versus Peer Users for Interpreting Laboratory Test Results for Lay Patients: Evaluation Study

BACKGROUND

Although patients have easy access to their electronic health records and laboratory test result data through patient portals, laboratory test results are often confusing and hard to understand. Many patients turn to web-based forums or question-and-answer (Q&A) sites to seek advice from their peers. The quality of answers from social Q&A sites on health-related questions varies significantly, and not all responses are accurate or reliable. Large language models (LLMs) such as ChatGPT have opened a promising avenue for patients to have their questions answered.

OBJECTIVE

We aimed to assess the feasibility of using LLMs to generate relevant, accurate, helpful, and unharmful responses to laboratory test-related questions asked by patients and identify potential issues that can be mitigated using augmentation approaches.

METHODS

We collected laboratory test result-related Q&A data from Yahoo! Answers and selected 53 Q&A pairs for this study. Using the LangChain framework and ChatGPT web portal, we generated responses to the 53 questions from 5 LLMs: GPT-4, GPT-3.5, LLaMA 2, MedAlpaca, and ORCA_mini. We assessed the similarity of their answers using standard Q&A similarity-based evaluation metrics, including Recall-Oriented Understudy for Gisting Evaluation, Bilingual Evaluation Understudy, Metric for Evaluation of Translation With Explicit Ordering, and Bidirectional Encoder Representations from Transformers Score. We used an LLM-based evaluator to judge whether a target model had higher quality in terms of relevance, correctness, helpfulness, and safety than the baseline model. We performed a manual evaluation with medical experts for all the responses to 7 selected questions on the same 4 aspects.

RESULTS

Regarding the similarity of the responses from 4 LLMs; the GPT-4 output was used as the reference answer, the responses from GPT-3.5 were the most similar, followed by those from LLaMA 2, ORCA_mini, and MedAlpaca. Human answers from Yahoo data were scored the lowest and, thus, as the least similar to GPT-4-generated answers. The results of the win rate and medical expert evaluation both showed that GPT-4's responses achieved better scores than all the other LLM responses and human responses on all 4 aspects (relevance, correctness, helpfulness, and safety). LLM responses occasionally also suffered from lack of interpretation in one's medical context, incorrect statements, and lack of references.

CONCLUSIONS

By evaluating LLMs in generating responses to patients' laboratory test result-related questions, we found that, compared to other 4 LLMs and human answers from a Q&A website, GPT-4's responses were more accurate, helpful, relevant, and safer. There were cases in which GPT-4 responses were inaccurate and not individualized. We identified a number of ways to improve the quality of LLM responses, including prompt engineering, prompt augmentation, retrieval-augmented generation, and response evaluation.

Metal-Graphene Hybrid Terahertz Metasurfaces for Circulating Tumor DNA Detection Based on Dual Signal Amplification

Terahertz (THz) spectroscopy has impressive capability for label-free biosensing, but its utility in clinical laboratories is rarely reported due to often unsatisfactory detection performances. Here, we fabricated metal-graphene hybrid THz metasurfaces (MSs) for the sensitive and enzyme-free detection of circulating tumor DNA (ctDNA) in pancreatic cancer plasma samples. The feasibility and mechanism of the enhanced effects of a graphene bridge across the MS and amplified by gold nanoparticles (AuNPs) were investigated experimentally and theoretically. The AuNPs serve to boost charge injection in the graphene film and result in producing a remarkable change in the graded transmissivity index to THz radiation of the MS resonators. Assay design utilizes this feature and a cascade hybridization chain reaction initiated on magnetic beads in the presence of target ctDNA to achieve dual signal amplification (chemical and optical). In addition to demonstrating subfemtomolar detection sensitivity and single-nucleotide mismatch selectivity, the proposed method showed remarkable capability to discriminate between pancreatic cancer patients and healthy individuals by recognizing and quantifying targeted ctDNAs. The introduction of graphene to the metasurface produces an improved sensitivity of 2 orders of magnitude for ctDNA detection. This is the first study to report the combined application of graphene and AuNPs in biosensing by THz spectroscopic resonators and provides a combined identification scheme to detect and discriminate different biological analytes, including nucleic acids, proteins, and various biomarkers.

Optimizing the indication of initial radioiodine oncolytic treatment for metastatic differentiated thyroid cancer by diagnostic 131I scan

AIM

As a classic theranostic radiopharmaceutical, radioiodine (131I) has been utilized in the management of differentiated thyroid cancer (DTC) for more than 8 decades, and the refinement of its clinical practice has been raised recently. This study was conducted to evaluate the efficiency of a diagnostic (Dx) 131I scan in optimizing the indication of initial radioiodine oncolytic treatment (ROT) for metastatic DTC by predicting therapeutic outcomes.

RESULTS

A total of 100 patients (Dx positive, n=29; Dx negative, n=71) were eligible for patient-based analysis. The matching rate was 83.0% between the Dx and the post-therapeutic scans (kappa = 0.648, P<0.001). The biochemical remission rate and structural shrinkage rate induced by the initial ROT in the Dx-positive group were, respectively, greater than those in the Dx-negative group (83.3% vs. 17.4%, P<0.001; 37.9% vs. 4.2%, P<0.001). Notably, the predictive values of positive Dx scans for ROT responsiveness and negative Dx scans for ROT nonresponsiveness reached up to 89.7% and 84.5%, respectively.

CONCLUSION

This Dx scan approach seems viable in characterizing the 131I-avidity of metastatic DTC and plays a pivotal role in optimizing the indication of initial ROT for metastatic DTC.

Assessing the Seasonality of Lab Tests Among Patients with Alzheimer's Disease and Related Dementias in OneFlorida Data Trust

About 1 in 9 older adults over 65 has Alzheimer's disease (AD), many of whom also have multiple other chronic conditions such as hypertension and diabetes, necessitating careful monitoring through laboratory tests. Understanding the patterns of laboratory tests in this population aids our understanding and management of these chronic conditions along with AD. In this study, we used an unimodal cosinor model to assess the seasonality of lab tests using electronic health record (EHR) data from 34,303 AD patients from the OneFlorida+ Clinical Research Consortium. We observed significant seasonal fluctuations-higher in winter in lab tests such as glucose, neutrophils per 100 white blood cells (WBC), and WBC. Notably, certain leukocyte types like eosinophils, lymphocytes, and monocytes are elevated during summer, likely reflecting seasonal respiratory diseases and allergens. Seasonality is more pronounced in older patients and varies by gender. Our findings suggest that recognizing these patterns and adjusting reference intervals for seasonality would allow healthcare providers to enhance diagnostic precision, tailor care, and potentially improve patient outcomes.

Quantum imaging of biological organisms through spatial and polarization entanglement

Quantum imaging holds potential benefits over classical imaging but has faced challenges such as poor signal-to-noise ratios, low resolvable pixel counts, difficulty in imaging biological organisms, and inability to quantify full birefringence properties. Here, we introduce quantum imaging by coincidence from entanglement (ICE), using spatially and polarization-entangled photon pairs to overcome these challenges. With spatial entanglement, ICE offers higher signal-to-noise ratios, greater resolvable pixel counts, and the ability to image biological organisms. With polarization entanglement, ICE provides quantitative quantum birefringence imaging capability, where both the phase retardation and the principal refractive index axis angle of an object can be remotely and instantly quantified without changing the polarization states of the photons incident on the object. Furthermore, ICE enables 25 times greater suppression of stray light than classical imaging. ICE has the potential to pave the way for quantum imaging in diverse fields, such as life sciences and remote sensing.

A time-averaged serum bicarbonate-based nomogram to predict the probability of residual kidney function preservation for patients undergoing peritoneal dialysis

OBJECTIVE

Residual kidney function (RKF) is an important prognostic indicator in peritoneal dialysis (PD) patients. So far, there are no prediction tools available for RKF, and the association between serum bicarbonate and RKF has received little attention in patients with PD. We aimed to develop a nomogram for the preservation of RKF based on the time-averaged serum bicarbonate (TA-Bic) levels.

PATIENTS AND METHODS

A prediction model was established by conducting a retrospective cohort study of 151 PD patients who had been treated at the First Affiliated Hospital of Anhui Medical University. The nomogram was developed using a multivariate Cox regression model. The discrimination, calibration, and clinical utility of the model were evaluated by the C-index, receiver operating curve (ROC) curve, calibration curve, and decision curve analysis.

RESULTS

In the elderly PD onset, higher baseline values of residual glomerular filtration rate, total Kt/V and higher TA-Bic levels were identified as protective predictors of RKF loss. The nomogram was conducted on the basis of the minimum value of the Akaike Information Criterion and Bayesian Information Criterion with a reasonable C-index of 0.766, showing great discrimination, proper calibration, and high potential for clinical practice. Through the total score of the nomogram, the patients were classified into the high-risk group and low-risk group, and a higher cumulative incidence of complete RRF loss was found in the high-risk group compared with the patients in the low-risk group.

CONCLUSIONS

The novel predictive nomogram model can predict the probability of RKF preservation in long-term PD patients with high accuracy. Future studies are needed to externally validate the current nomogram before clinical application.

Circ_ST6GAL1-mediated competing endogenous RNA network regulates TGF-β1-stimulated matrix Metalloproteinase-13 expression via Runx2 acetylation in osteoblasts

Transforming growth factor-beta1 (TGF-β1) stimulates matrix metalloproteinase-13 (MMP-13, a bone-remodeling gene) expression, and this effect requires p300-mediated Runx2 (Runt-related transcription factor 2) acetylation in osteoblasts. p300 and Runx2 are transcriptional coactivator and bone transcription factor, respectively, which play key roles in the regulation of bone-remodeling genes. Non-coding ribonucleic acids (ncRNAs), such as long ncRNAs (lncRNAs) and microRNAs (miRNAs), have been linked to both physiological and pathological bone states. In this study, we proposed that TGF-β1-mediated stimulation of MMP-13 expression is due to the downregulation of p300 targeting miRNAs in osteoblasts. We identified miR-130b-5p as one of the miRNAs downregulated by TGF-β1 in osteoblasts. Forced expression of miR-130b-5p decreased p300 expression, Runx2 acetylation, and MMP-13 expression in these cells. Furthermore, TGF-β1 upregulated circ_ST6GAL1, (a circular lncRNA) in osteoblasts; circRNA directly targeted miR-130b-5p. Antisense-mediated knockdown of circ_ST6GAL1 restored the function of miR-130b-5p, resulting in downregulation of p300, Runx2, and MMP-13 in these cells. Hence, our results suggest that TGF-β1 influences circ_ST6GAL1 to sponge and degrade miR-130b-5p, thereby promoting p300-mediated Runx2 acetylation for MMP-13 expression in osteoblasts. Thus, the circ_ST6GAL1/miR-130b-5p/p300 axis has potential significance in the treatment of bone and bone-related disorders.

Quality of Answers of Generative Large Language Models vs Peer Patients for Interpreting Lab Test Results for Lay Patients: Evaluation Study

Lab results are often confusing and hard to understand. Large language models (LLMs) such as ChatGPT have opened a promising avenue for patients to get their questions answered. We aim to assess the feasibility of using LLMs to generate relevant, accurate, helpful, and unharmful responses to lab test-related questions asked by patients and to identify potential issues that can be mitigated with augmentation approaches. We first collected lab test results related question and answer data from Yahoo! Answers and selected 53 QA pairs for this study. Using the LangChain framework and ChatGPT web portal, we generated responses to the 53 questions from four LLMs including GPT-4, Meta LLaMA 2, MedAlpaca, and ORCA_mini. We first assessed the similarity of their answers using standard QA similarity-based evaluation metrics including ROUGE, BLEU, METEOR, BERTScore. We also utilized an LLM-based evaluator to judge whether a target model has higher quality in terms of relevance, correctness, helpfulness, and safety than the baseline model. Finally, we performed a manual evaluation with medical experts for all the responses to seven selected questions on the same four aspects. The results of Win Rate and medical expert evaluation both showed that GPT-4's responses achieved better scores than all the other LLM responses and human responses on all four aspects (relevance, correctness, helpfulness, and safety). However, LLM responses occasionally also suffer from a lack of interpretation in one's medical context, incorrect statements, and lack of references. We find that compared to other three LLMs and human answer from the Q&A website, GPT-4's responses are more accurate, helpful, relevant, and safer. However, there are cases which GPT-4 responses are inaccurate and not individualized. We identified a number of ways to improve the quality of LLM responses.

Annotation and Information Extraction of Consumer-Friendly Health Articles for Enhancing Laboratory Test Reporting

Viewing laboratory test results is patients' most frequent activity when accessing patient portals, but lab results can be very confusing for patients. Previous research has explored various ways to present lab results, but few have attempted to provide tailored information support based on individual patient's medical context. In this study, we collected and annotated interpretations of textual lab result in 251 health articles about laboratory tests from AHealthyMe.com. Then we evaluated transformer-based language models including BioBERT, ClinicalBERT, RoBERTa, and PubMedBERT for recognizing key terms and their types. Using BioPortal's term search API, we mapped the annotated terms to concepts in major controlled terminologies. Results showed that PubMedBERT achieved the best F1 on both strict and lenient matching criteria. SNOMED CT had the best coverage of the terms, followed by LOINC and ICD-10-CM. This work lays the foundation for enhancing the presentation of lab results in patient portals by providing patients with contextualized interpretations of their lab results and individualized question prompts that they can, in turn, refer to during physician consults.

A Thermus thermophilus argonaute-coupling exponential amplification assay for ultrarapid analysis of circulating tumor DNA

Circulating tumor DNA (ctDNA) is a noninvasive biomarker for liquid biopsy with important clinical and biological information, but existing detection techniques are expensive, complex and quite time-consuming. Here, we report an ultrarapid, sensitive and simple method, which we term Thermus thermophilus argonaute-coupling exponential amplification reaction (TtAgo-CEAR), that selectively amplifies mutated ctDNA. Aiming at seven Kirsten rat sarcoma-2 virus (KRAS) point mutations, the present strategy allows for easy detection with attomolar sensitivity and single-nucleotide specificity within as little as 16 min without prior PCR amplification. We also demonstrate that TtAgo-coupling assay is easily adaptable to Terahertz spectroscopy-based and lateral-flow-based readout. We show that the detected ctDNA concentrations by mouse models can respond to the variations of disease burden in serum samples. It is envisioned that this TtAgo-CEAR approach has great potential for rapid diagnosis and monitoring of diverse malignant tumors.

Adherence Promotion With Tailored Motivational Messages: Proof of Concept and Message Preferences in Older Adults

This study examined the feasibility of using tailored text messages to promote adherence to longitudinal protocols and determined what facets of text message tone influence motivation. Forty-three older adults (Mage = 73.21, SD = 5.37) were recruited to engage in video-game-based cognitive training for 10 consecutive days. Participants received encouraging text messages each morning that matched their highest or lowest ranking reasons for participating in the study, after which they rated how effective each message was in motivating them to play the games that day. After 10 days, participants rated all possible messages and participated in semi-structured interviews to elicit their preferences for these messages. Results showed that messages matching participants' reasons for participating were more motivating than mismatched messages. Further, participants preferred messages that were personalized (i.e., use second person voice) and in formal tones. Messages consistent with these preferences were also rated as more motivating. These findings establish the feasibility of using message tailoring to promote adherence to longitudinal protocols and the relevance of tailoring messages to be personal and formal.

Big advocacy, little recognition: the hidden work of Black patients in precision medicine

As cost-effective next-generation genome sequencing rapidly develops, calls for greater inclusion of Black people in genomic research, policy, and practice are necessary for effective translation of genomic science into precision population health and medicine. Employing a community-based participatory mixed methods research design, we developed a semi-structured survey that was disseminated to three cancer advocacy organizations. Of the 81 survey respondents 49 (60%) self-identified as Black, and 26 (32%) indicated a prior breast cancer diagnosis. Black participants' expressed concerns about genetic testing were evenly distributed between concerns that could be addressed through genetic counseling (24%) and concerns about subsequent use of their genetic data (27%). Patient advocates contributed to contextualization of respondent concerns in terms of community experiences. Although genetic counseling services and policies governing genomic data use are not always accessible to many Black communities, advocates on our research team provided a bridge to discussion of the intersection between respondent concerns and the roles advocates play in filling gaps in access to genetic counseling and data governance. Concerns expressed by Black patients underscore a shared need among all patients for access to education, inclusion in research, and assurances regarding the use and handling of genetic data. Black cancer patients have joined in patient-led efforts to overcome systemic inequities in cancer care to improve their health outcomes through representation. Often their efforts are overshadowed by a relentless burden of continued health disparities. Future research should support their hidden work as a means to reduce barriers and improve representation in genomic databases.

Effects of lysolecithins on performance, egg quality, blood profiles and liver histopathology in late-phase laying hens

1. This study investigated the effects of lysolecithins (LL) on performance, egg quality, blood profiles, relative organ weight and liver histopathology in laying hens.2. A total of 480 healthy 65-week-old Lohmann laying hens were randomly allocated into four treatments in a 2 × 2 factorial arrangement design with two levels of energy (AMEn, 11.08 MJ/kg and 12.94 MJ/kg) and two levels of LL (0 and 0.05%).3. Birds fed high energy diets had lower (P < 0.05) average daily intake and feed conversion rate during weeks 0-4, 5-8 and 0-8, but higher (P < 0.05) average egg weight (AEW) during trial weeks 0-4. There was an interaction in (P < 0.05) AEW during trial weeks 0-14 and 0-8 for energy and LL. The high energy diets increased yolk colour at the end of weeks 2 and 4, while addition of LL increased albumen height at the end of week 2. There was an interaction (P < 0.05) in yolk colour between energy and LL at the end of week 2. There was an interaction (P < 0.05) in serum superoxide dismutase and LDL-C throughout the experiment.4. The high energy diets increased (P < 0.05) the relative weight of abdominal fat compared with low energy diets. The high energy diets increased (P < 0.05) liver ether extract content and liver pathological injury score compared with low energy diets at the end of week 8, while the addition of LL decreased (P < 0.05) liver pathological injury score.5. The supplementation of LL in high energy diets could alleviate some negative effects on liver injury in late laying hens.

A Novel Optical Fiber Terahertz Biosensor Based on Anti-Resonance for The Rapid and Nondestructive Detection of Tumor Cells

The sensitive and accurate detection of tumor cells is essential for successful cancer therapy and improving cancer survival rates. However, current tumor cell detection technologies have some limitations for clinical applications due to their complexity, low specificity, and high cost. Herein, we describe the design of a terahertz anti-resonance hollow core fiber (THz AR-HCF) biosensor that can be used for tumor cell detection. Through simulation and experimental comparisons, the low-loss property of the THz AR-HCF was verified, and the most suitable fiber out of multiple THz AR-HCFs was selected for biosensing applications. By measuring different cell numbers and different types of tumor cells, a good linear relationship between THz transmittance and the numbers of cells between 10 and 106 was found. Meanwhile, different types of tumor cells can be distinguished by comparing THz transmission spectra, indicating that the biosensor has high sensitivity and specificity for tumor cell detection. The biosensor only required a small amount of sample (as low as 100 μL), and it enables label-free and nondestructive quantitative detection. Our flow cytometry results showed that the cell viability was as high as 98.5 ± 0.26% after the whole assay process, and there was no statistically significant difference compared with the negative control. This study demonstrates that the proposed THz AR-HCF biosensor has great potential for the highly sensitive, label-free, and nondestructive detection of circulating tumor cells in clinical samples.

[Impact of COVID-19 pandemic on the management of imported malaria in China]

OBJECTIVE

To examine the impact of COVID-19 pandemic on the epidemic status of imported malaria and national malaria control program in China, so as to provide insights into post-elimination malaria surveillance.

METHODS

All data pertaining to imported malaria cases were collected from Anhui Province, Hubei Province, Henan Province, Zhejiang Province and Guangxi Zhuang Autonomous Region during the period from January 1, 2018 through December 31, 2021. The number of malaria cases, species of malaria parasites, country where malaria parasite were infected, diagnosis and treatment after returning to China, and response were compared before (from January 1, 2018 to January 22, 2020) and after the COVID-19 pandemic (from January 23, 2020 to December 31, 2021).

RESULTS

A total of 2 054 imported malaria cases were reported in Anhui Province, Hubei Province, Henan Province, Zhejiang Province and Guangxi Zhuang Autonomous Region during the period from January 1, 2018 to December 31, 2021, and there were 1 722 cases and 332 cases reported before and after the COVID-19 pandemic, respectively. All cases were reported within one day after definitive diagnosis. The annual mean number of reported malaria cases reduced by 79.30% in Anhui Province, Hubei Province, Henan Province, Zhejiang Province and Guangxi Zhuang Autonomous Region after the COVID-19 pandemic (171 cases) than before the pandemic (826 cases), and the number of monthly reported malaria cases significantly reduced in Anhui Province, Hubei Province, Henan Province, Zhejiang Province and Guangxi Zhuang Autonomous Region since February 2020. There was a significant difference in the constituent ratio of species of malaria parasites among the imported malaria cases in Anhui Province, Hubei Province, Henan Province, Zhejiang Province and Guangxi Zhuang Autonomous Region before and after the COVID-19 pandemic (χ2 = 146.70, P < 0.05), and P. falciparum malaria was predominant before the COVID-19 pandemic (72.30%), while P. ovale malaria (44.28%) was predominant after the COVID-19 pandemic, followed by P. falciparum malaria (37.65%). There was a significant difference in the constituent ratio of country where malaria parasites were infected among imported malaria cases in Anhui Province, Hubei Province, Henan Province, Zhejiang Province and Guangxi Zhuang Autonomous Region before and after the COVID-19 pandemic (χ2 = 13.83, P < 0.05), and the proportion of malaria cases that acquired Plasmodium infections in western Africa reduced after the COVID-19 pandemic that before the pandemic (44.13% vs. 37.95%; χ2 = 4.34, P < 0.05), while the proportion of malaria cases that acquired Plasmodium infections in eastern Africa increased after the COVID-19 pandemic that before the pandemic (9.58% vs. 15.36%; χ2 = 9.88, P = 0.02). The proportion of completing case investigation within 3 days was significantly lower after the COVID-19 pandemic than before the pandemic (96.69% vs. 98.32%; χ2= 3.87, P < 0.05), while the proportion of finishing foci investigation and response within 7 days was significantly higher after the COVID-19 pandemic than before the pandemic (100.00% vs. 98.43%; χ2 = 3.95, P < 0.05).

CONCLUSIONS

The number of imported malaria cases remarkably reduced in Anhui Province, Hubei Province, Henan Province, Zhejiang Province and Guangxi Zhuang Autonomous Region of China during the COVID-19 pandemic, with a decreased proportion of completing case investigations within 3 days. The sensitivity of the malaria surveillance-response system requires to be improved to prevent the risk of secondary transmission of malaria due to the sharp increase in the number of imported malaria cases following the change of the COVID-19 containment policy.

Phase II Multi-Institutional Study of a Low-Dose (4 Gy) Palliative Response-Adapted Radiotherapy Regimen for Symptomatic Bone Metastases from Multiple Myeloma: Planned Interim Analysis of First 40 Patients

PURPOSE/OBJECTIVE(S)

Painful bone lesions are common in patients with multiple myeloma (MM). Radiotherapy (RT) is effective in providing pain relief from MM bone lesions in over 80% of patients. There is no consensus as to the most effective dose or fractionation for palliation. Shorter courses of therapy are not only more convenient for patients, but they also have less impact on timing of systemic therapies. There is precedent for using 4 Gy in the palliation of lymphomas, which have similar radiosensitivity to myeloma. The primary objective of this trial is to determine whether treatment with a total dose of 4 Gy to a painful myeloma bone lesion achieves patient-reported pain reduction comparable to historical controls at 4 weeks.

MATERIALS/METHODS

Patients with a known diagnosis of MM and a painful bone lesion that was not at the base of skull, in need of stabilization, or causing cord compression were treated with 4 Gy (2 Gy x 2 or 4 Gy x 1). Patients' pain was measured using the brief pain index (BPI) prior to treatment and at 2, 4, 8 weeks and 6 months following treatment. Pain response was determined by the international consensus on palliative radiotherapy and considered change in BPI and oral morphine equivalent dose (OMED). A planned interim analysis for futility was completed after 40 patients. Reirradiation with clinician choice regimens could be considered at ≥4 weeks following initial treatment for indeterminate pain response or pain progression.

RESULTS

Forty patients were treated at 6 institutions between 2019 and 2022. Median age was 65 years with 40% women and 88% with an ECOG of 0-1. A complete response (CR) was defined as a BPI score of 0 with no concomitant increase in OMED. A partial response (PR) was defined as BPI reduction in 2 or more without analgesic increase, or an OMED reduction of 25% or more without an increase in pain. An indeterminate response (IR) was any response that is not captured by a CR, PR or pain progression. A CR was achieved in 48%, a PR in 38% of patients, an IR in 13% with 1 patient who refused participation. Pain response was achieved in 86% of patients. Seven patients (18%) requested reirradiation at ≥4 weeks. Median BPI at baseline and 4 weeks after RT for patients with CR, PR, and IR were 3.75 and 0, 4.00 and 1, and 5.25 and 4.75, respectively. Median change of BPI between baseline and 4 weeks after RT for all responders (CR and PR) was -3.25. The median PTV volume (cc) for patients with CR, PR and IR were 81, 140 and 226, respectively. Based on these results, the futility threshold was not met, and the recommendation by the DSMC is to continue the trial.

CONCLUSION

In the first 40 patients who received 4 Gy palliation for painful bone lesions from multiple myeloma, there were 86% that had a pain response (48% CR, 38% PR). This low dose, response-adapted treatment, led to reirradiation in less than 20% of patients.

[Molecular detection and phylogenetic analysis of Wolbachia infection in common mosquito species in Henan Province]

OBJECTIVE

To investigate the infection and genotypes of Wolbachia in common mosquito species in Henan Province, so as to provide insights into management of mosquito-borne diseases.

METHODS

Aedes, Culex and Anopheles samples were collected from cowsheds, sheepfolds and human houses in Puyang, Nanyang City and Xuchang cities of Henan Province from July to September, 2022, and the infection of Wolbachia was detected. The 16S rDNA and wsp genes of Wolbachia were amplified and sequenced. Sequence alignment was performed using the BLAST software, and the obtained 16S rDNA gene sequence was compared with the sequence of the 16S rDNA gene in GenBank database. In addition, the phylogenetic trees were created based on 16S rDNA and wsp gene sequences using the software MEGA 11.0.

RESULTS

A total 506 female adult mosquitoes were collected from three sampling sites in Nanyang, Xuchang City and Puyang cities from July to September, 2022. The overall detection of Wolbachia was 45.1% (228/506) in mosquitoes, with a higher detection rate in A. albopictus than in Cx. pipiens pallens [97.9% (143/146) vs. 50.6% (85/168); χ2 = 88.064, P < 0.01]. The detection of Wolbachia in Cx. pipiens pallens was higher in Xuchang City (96.8%, 62/64) than in Nanyang (15.6%, 7/45) and Puyang cities (27.1%, 16/59) (χ2 = 89.950, P < 0.01). The homologies of obtained Wolbachia 16S rDNA and wsp gene sequences were 95.3% to 100.0% and 81.7% to 99.8%. Phylogenetic analysis based on wsp gene sequences showed Wolbachia supergroups A and B in mosquito samples, with wAlbA and wMors strains in supergroup A and wPip and wAlbB strains in supergroup B. Wolbachia strain wAlbB infection was detected in A. albopictus in Puyang and Nanyang Cities, while Wolbachia strain wPip infection was identified in A. albopictus in Xuchang City. Wolbachia strain wAlbA infection was detected in Cx. pipiens pallens sampled from three cities, and one Cx. pipiens pallens was found to be infected with Wolbachia strain wMors in Nanyang City.

CONCLUSIONS

Wolbachia infection is commonly prevalent in Ae. albopictus and Cx. pipiens pallens from Henan Province, and Wolbachia strains wAlbB and wAlbA are predominant in Ae. albopictus, while wPip strain is predominant in Cx. pipiens pallens. This is the first report to present Wolbachia wMors strain infection in Cx. pipiens pallens in Henan Province.

Effects of Straw Mulching on Soil Properties and Enzyme Activities of Camellia oleifera-Cassia Intercropping Agroforestry Systems

In order to explore the influences of rice straw mulching on soil fertility in agroforestry systems, the soil C and N contents and enzyme activities were investigated in a C. oleifera-cassia intercropping ecosystem in Central Southern China. Three straw mulching application treatments were set up in this study, in 2021, namely, straw powder mulching (SPM), straw segment mulching (SSM), and non-straw mulching as the control (CK). Soil samples were collected from three soil depths (0-10 cm,10-20 cm, and 20-40 cm) in each treatment on the 90th-day after the treatments. The soil organic carbon (SOC), total nitrogen (TN), microbial carbon (MBC), soil enzyme activities (including acid phosphatase (ACP), urease (UE), cellulase (CL), and peroxidase (POD)), and soil water content (SWC) were determined. The results showed that the SOC significantly increased due to the mulching application in SPM and SSM, in the topsoil of 0-10 cm when compared to the CK. The SWC, SOC, TN, and MBC increased by 0.8 and 56.5, 3.5 and 37.5, 21.3 and 61.6, and 5.8% and 76.8% in the SPM and SSM treatments compared to the CK, respectively. The soil enzyme activities of ACP, UE, CE, and POD increased significantly due to straw mulching compared with CK throughout all soil layers. The soil enzyme activities of CL and POD were significantly higher in SSM than in SPM across the soil depth except for ACP. The enzyme activities of ACP were 14,190, 12,732, and 6490 U/g in SSM, SPM, and control, respectively. This indicated that mulching application enhanced the enzyme activity of ACP. Mulching had no significant effects on UE and CL, while the POD decreased significantly in the order of SPM > SSM > CK across all soil layers, being, on average, 6.64% and 3.14% higher in SSM and SPM, respectively, compared to the CK plots. The SOC and MBC were the key nutrient factors affecting the soil enzyme activities at the study site. The results from this study provided Important scientific insights for improving soil physicochemical properties during the management of the C. oleifera intercropping system and for the development of the C. oleifera industry.

Enriching Real-world Data with Social Determinants of Health for Health Outcomes and Health Equity: Successes, Challenges, and Opportunities

OBJECTIVE

To summarize the recent methods and applications that leverage real-world data such as electronic health records (EHRs) with social determinants of health (SDoH) for public and population health and health equity and identify successes, challenges, and possible solutions.

METHODS

In this opinion review, grounded on a social-ecological-model-based conceptual framework, we surveyed data sources and recent informatics approaches that enable leveraging SDoH along with real-world data to support public health and clinical health applications including helping design public health intervention, enhancing risk stratification, and enabling the prediction of unmet social needs.

RESULTS

Besides summarizing data sources, we identified gaps in capturing SDoH data in existing EHR systems and opportunities to leverage informatics approaches to collect SDoH information either from structured and unstructured EHR data or through linking with public surveys and environmental data. We also surveyed recently developed ontologies for standardizing SDoH information and approaches that incorporate SDoH for disease risk stratification, public health crisis prediction, and development of tailored interventions.

CONCLUSIONS

To enable effective public health and clinical applications using real-world data with SDoH, it is necessary to develop both non-technical solutions involving incentives, policies, and training as well as technical solutions such as novel social risk management tools that are integrated into clinical workflow. Ultimately, SDoH-powered social risk management, disease risk prediction, and development of SDoH tailored interventions for disease prevention and management have the potential to improve population health, reduce disparities, and improve health equity.

Detecting and characterizing special nuclear material for nuclear nonproliferation applications

There is an urgent need for new, better instrumentation and techniques for detecting and characterizing special nuclear material (SNM), i.e., highly enriched uranium and plutonium. The development of improved instruments and techniques requires experiments performed with the SNM itself, which is of limited availability. This paper describes the findings of experiments performed at the National Criticality Experiments Research Center conducted using new instruments and techniques on unclassified, kg-quantity SNM objects. These experiments, performed in the framework of the Department of Energy, National Nuclear Security Administration Consortium for Monitoring, Technology, and Verification, focused on detecting, characterizing, and localizing SNM samples with masses ranging from 3.3 to 13.8 kg, including plutonium and highly enriched uranium using prototype detectors and techniques. The work demonstrates SNM detection and characterization using recently-developed prototype detection systems. Specifically, we present new results in passive detection and imaging of plutonium and uranium objects using gamma-ray and dual particle (fast neutron and gamma-ray) imaging. We also present a new analysis of the delayed neutron emissions during active interrogation of uranium using a neutron generator.

Prediction of Outcomes After Heart Transplantation in Pediatric Patients Using National Registry Data: Evaluation of Machine Learning Approaches

BACKGROUND

The prediction of posttransplant health outcomes for pediatric heart transplantation is critical for risk stratification and high-quality posttransplant care.

OBJECTIVE

The purpose of this study was to examine the use of machine learning (ML) models to predict rejection and mortality for pediatric heart transplant recipients.

METHODS

Various ML models were used to predict rejection and mortality at 1, 3, and 5 years after transplantation in pediatric heart transplant recipients using United Network for Organ Sharing data from 1987 to 2019. The variables used for predicting posttransplant outcomes included donor and recipient as well as medical and social factors. We evaluated 7 ML models-extreme gradient boosting (XGBoost), logistic regression, support vector machine, random forest (RF), stochastic gradient descent, multilayer perceptron, and adaptive boosting (AdaBoost)-as well as a deep learning model with 2 hidden layers with 100 neurons and a rectified linear unit (ReLU) activation function followed by batch normalization for each and a classification head with a softmax activation function. We used 10-fold cross-validation to evaluate model performance. Shapley additive explanations (SHAP) values were calculated to estimate the importance of each variable for prediction.

RESULTS

RF and AdaBoost models were the best-performing algorithms for different prediction windows across outcomes. RF outperformed other ML algorithms in predicting 5 of the 6 outcomes (area under the receiver operating characteristic curve [AUROC] 0.664 and 0.706 for 1-year and 3-year rejection, respectively, and AUROC 0.697, 0.758, and 0.763 for 1-year, 3-year, and 5-year mortality, respectively). AdaBoost achieved the best performance for prediction of 5-year rejection (AUROC 0.705).

CONCLUSIONS

This study demonstrates the comparative utility of ML approaches for modeling posttransplant health outcomes using registry data. ML approaches can identify unique risk factors and their complex relationship with outcomes, thereby identifying patients considered to be at risk and informing the transplant community about the potential of these innovative approaches to improve pediatric care after heart transplantation. Future studies are required to translate the information derived from prediction models to optimize counseling, clinical care, and decision-making within pediatric organ transplant centers.

Towards Interpretable Multimodal Predictive Models for Early Mortality Prediction of Hemorrhagic Stroke Patients

The increasing death rate over the past eight years due to stroke has prompted clinicians to look for data-driven decision aids. Recently, deep-learning-based prediction models trained with fine-grained electronic health record (EHR) data have shown superior promise for health outcome prediction. However, the use of EHR-based deep learning models for hemorrhagic stroke outcome prediction has not been extensively explored. This paper proposes an ensemble deep learning framework to predict early mortality among ICU patients with hemorrhagic stroke. The proposed ensemble model achieved an accuracy of 83%, which was higher than the fusion model and other baseline models (logistic regression, decision tree, random forest, and XGBoost). Moreover, we used SHAP values for interpretation of the ensemble model to identify important features for the prediction. In addition, this paper follows the MINIMAR (MINimum Information for Medical AI Reporting) standard, presenting an important step towards building trust among the AI system and clinicians.

Benchmarking Transformer-Based Models for Identifying Social Determinants of Health in Clinical Notes

Electronic health records (EHR) have been widely used in building machine learning models for health outcomes prediction. However, many EHR-based models are inherently biased due to lack of risk factors on social determinants of health (SDoH), which are responsible for up to 40% preventive deaths. As SDoH information is often captured in clinical notes, recent efforts have been made to extract such information from notes with natural language processing and append it to other structured data. In this work, we benchmark 7 pre-trained transformer-based models, including BERT, ALBERT, BioBERT, BioClinicalBERT, RoBERTa, ELECTRA, and RoBERTa-MIMIC-Trial, for recognizing SDoH terms using a previously annotated corpus of MIMIC-III clinical notes. Our study shows that BioClinicalBERT model performs best on F-1 scores (0.911, 0.923) under both strict and relaxed criteria. This work shows the promise of using transformer-based models for recognizing SDoH information from clinical notes.

Improving Adherence to a Mediterranean Ketogenic Nutrition Program for High-Risk Older Adults: A Pilot Randomized Trial

(1) Background: Mediterranean ketogenic nutrition (MKN) may directly target multiple neurobiological mechanisms associated with dementia risk in older adults. Despite its promise, this type of nutrition can be challenging to learn and adhere to in a healthy manner. Our team used the National Institutes of Health Obesity Related Behavioral Intervention Trials (NIH ORBIT) model to develop and pilot a program to help older adults with memory concerns use MKN. (2) Methods: Using a two-arm, randomized design, we evaluated an MKN Adherence (MKNA) program compared to an MKN education (MKNE) program (N = 58). The primary difference between study arms involved the use of motivational interviewing (MI) strategies and behavior change techniques (BCT) only in the MKNA arm. Participants were included if they evidenced subjective memory concerns or objective memory impairment on the Montreal Cognitive Assessment (Score 19 ≤ 26). Primary outcomes examined included feasibility, acceptability, adherence, and clinical outcomes associated with the program. (3) Results: Overall, there was relatively high program completion in both groups, with 79% of participants completing the 6-week program. The recruitment protocol required adjustment but was successful in reaching the target sample size. Retention (82%) and session attendance (91%) were higher in the MKNA arm compared to the MKNE (retention = 72%; attendance = 77%). Overall, most participants in both groups rated the program as "excellent" using the client satisfaction questionnaire. Participants in the MKNA arm evidenced higher objective and self-reported adherence to MKN during the 6-week program. Further, there was some evidence of clinical benefits of the program, although these effects diminished as adherence decreased in the 3 months follow-up. (4) Discussion: This pilot trial demonstrated that the MKN program incorporating MI and BCT strategies may better engage and retain participants than a nutrition education program alone, although participants in both groups reported high satisfaction.

Quantum microscopy of cells at the Heisenberg limit

Entangled biphoton sources exhibit nonclassical characteristics and have been applied to imaging techniques such as ghost imaging, quantum holography, and quantum optical coherence tomography. The development of wide-field quantum imaging to date has been hindered by low spatial resolutions, speeds, and contrast-to-noise ratios (CNRs). Here, we present quantum microscopy by coincidence (QMC) with balanced pathlengths, which enables super-resolution imaging at the Heisenberg limit with substantially higher speeds and CNRs than existing wide-field quantum imaging methods. QMC benefits from a configuration with balanced pathlengths, where a pair of entangled photons traversing symmetric paths with balanced optical pathlengths in two arms behave like a single photon with half the wavelength, leading to a two-fold resolution improvement. Concurrently, QMC resists stray light up to 155 times stronger than classical signals. The low intensity and entanglement features of biphotons in QMC promise nondestructive bioimaging. QMC advances quantum imaging to the microscopic level with significant improvements in speed and CNR toward the bioimaging of cancer cells. We experimentally and theoretically prove that the configuration with balanced pathlengths illuminates an avenue for quantum-enhanced coincidence imaging at the Heisenberg limit.

Molecular cloning, expression analysis and functional characterization of chicken cytochrome P450 27A1: A novel mitochondrial vitamin D3 25-hydroxylase

Vitamin D₃ is hydroxylated by cytochrome P450 (CYP) before exerting biological effects. The chicken CYP involved in vitamin D₃ 25-hydroxylation has yet to be cloned, and little is known about its functional characteristics, tissue distribution, and cellular expression. We identified a novel, full-length CYP27A1 gene cloned from chicken hepatocyte cDNA that encodes a putative protein of 518 amino acids. Swiss modeling revealed that chicken CYP27A1 has a classic open-fold form. Multisequence homology alignment determined that CYP27A1 contains conserved motifs for substrate recognition and binding. Quantitative real-time PCR analysis in 2-mo-old Partridge Shank broilers demonstrated that CYP27A1 mRNA levels were highest in the liver, followed by the thigh muscles, the breast muscles, and kidneys. The transcripts of CYP27A1 in breast muscles were significantly higher in males than in females. A subcellular localization analysis demonstrated that CYP27A1 was mainly expressed in the mitochondria. In vitro enzyme assays suggested that recombinant CYP27A1 hydroxylates vitamin D₃ at the C-25 position to form 25-hydroxyvitamin D₃ (25(OH)D₃). The K_m and V_max values for CYP27A1-dependent vitamin D₃ 25-hydroxylation were estimated to be 4.929 μM and 0.389 mol min^-1 mg^-1 protein, respectively. In summary, these results suggest that CYP27A1 encodes a mitochondrial CYP that plays an important physiologic role in the 25-hydroxylation of vitamin D₃ in chickens, providing novel insights into vitamin D₃ metabolism in this species.

Big Advocacy, Little Recognition: The Hidden Work of Black Patients in Precision Medicine

Public health genomics prioritizes effective and ethical translation of genomic science into population health precision medicine. With the rapid development of cost-effective, next-generation genome sequencing, calls are growing for greater inclusion of Black people in genomic research, policy, and practice. Genetic testing is often the first step in precision medicine. This study explores racial differences in patient concerns about genetic testing for hereditary breast cancer. Employing a community-based participatory mixed methods research design, we developed a semi-structured survey that was shared broadly. There were 81 survey respondents, of which, forty-nine (60%) self-identified as Black, twenty-six (32%) indicated they had a history of a breast cancer diagnosis, or had received BRCA genetic testing. Black participants who expressed concerns about genetic testing were fairly equally distributed between concerns that could be addressed with genetic counseling (24%) and concerns about the subsequent use of their genetic data (27%). The concerns expressed by the participants in our study underscore a need for transparent disclosures and assurances regarding the use and handling of genetic data. These findings should be viewed in context with patient-led efforts to overcome systemic inequities in cancer care, as Black cancer patients have joined forces with advocates and researchers to develop protective health data initiatives and to improve their representation in genomic datasets. Future research should prioritize the information needs and concerns of Black cancer patients. Interventions should be developed to support their hidden work as a means to reduce barriers and improve representation in precision medicine.

[Effects of staged acupuncture on endometrial receptivity and anxiety in patients with recurrent implantation failure of thin endometrium based on "thoroughfare vessel is the sea of blood" theory]

OBJECTIVE

To compare the clinical efficacy between staged acupuncture based on "thoroughfare vessel is the sea of blood" theory combined with routine hormone replacement cycle treatment and routine hormone replacement cycle treatment for patients with recurrent implantation failure (RIF) of thin endometrium.

METHODS

A total of 72 RIF patients with thin endometrium were randomly divided into an observation group and a control group, 36 cases in each group. The patients in the control group were treated with routine hormone replacement cycle treatment. Based on the treatment of the control group, the patients in the observation group were treated with staged acupuncture based on "thoroughfare vessel is the sea of blood" theory. The main acupoints were Neiguan (PC 6) and Gongsun (SP 4), and the supplementary acupoints were selected according to the menstrual cycle and syndrome differentiation; the acupuncture was given once every other day, 3 times a week, for 3 consecutive menstrual cycles. The thickness and shape of endometrium, and Hamilton anxiety scale (HAMA) score were observed at implantation window before and after treatment; the clinical pregnancy rate, live birth rate and cycle cancellation rate were compared between the two groups; the correlation between endometrial thickness and HAMA score was analyzed.

RESULTS

Compared before treatment, the endometrial thickness in the two groups and the proportion of type A+B endometrium in the observation group were increased (P<0.05), and the HAMA scores in the two groups were decreased (P<0.05) after treatment. The above indexes in the observation group were superior to those in the control group (P<0.05). The clinical pregnancy rate and live birth rate in the observation group were higher than those in the control group (P<0.05), and the cycle cancellation rate was lower than that in the control group (P<0.05). There was a negative correlation between endometrial thickness and HAMA score (P<0.05).

CONCLUSION

Based on the routine hormone replacement cycle treatment, the addition use of staged acupuncture based on "thoroughfare vessel is the sea of blood" theory could improve the thickness and shape of endometrium, relieve anxiety, increase the clinical pregnancy rate and live birth rate, and reduce the cycle cancellation rate in RIF patients with thin endometrium. The curative effect is superior to the routine hormone replacement cycle treatment alone.

Experimental full-domain mapping of quantum correlation in Clauser-Horne-Shimony-Holt scenarios

Quantum correlation between two parties serves as an important resource in the surging applications of quantum information. The Bell nonlocality and quantum steering have been proposed to describe non-classical correlations against local-hidden-variable and local-hidden-state theories, respectively. To characterize the two types of non-classical correlations, various nonlocality and steering inequalities have been established, and the amount of inequality violation serves as an important indicator for many entanglement-based tasks. Quantum state tomography has been employed for measuring quantum states, while the method requires intensive computation and does not directly verify either nonlocality or steering over the full domain independent of established theories. Here, we experimentally map the full-domain correlation with bipartite states for nonlocality and quantum steering in CHSH scenarios. The measurement of the maps automatically accounts for detection imperfections. Furthermore, we demonstrate the application of the correlation maps in the entanglement-based quantum key distribution protocol with arbitrary bipartite states. The correlation maps show direct measurements and simple interpretations that can answer fundamental questions about nonlocality and quantum steering as well as contribute to quantum information applications in a straightforward manner.

[Fibroblasts overpressing WNT2b cause impairment of intestinal mucosal barrier]

OBJECTIVE

To investigate the mechanism by which fibroblasts with high WNT2b expression causes intestinal mucosa barrier disruption and promote the progression of inflammatory bowel disease (IBD).

METHODS

Caco-2 cells were treated with 20% fibroblast conditioned medium or co-cultured with fibroblasts highly expressing WNT2b, with the cells without treatment with the conditioned medium and cells co-cultured with wild-type fibroblasts as the control groups. The changes in barrier permeability of Caco-2 cells were assessed by measuring transmembrane resistance and Lucifer Yellow permeability. In Caco-2 cells co-cultured with WNT2b-overexpressing or control intestinal fibroblasts, nuclear entry of β-catenin was detected with immunofluorescence assay, and the expressions of tight junction proteins ZO-1 and E-cadherin were detected with Western blotting. In a C57 mouse model of dextran sulfate sodium (DSS)-induced IBD-like enteritis, the therapeutic effect of intraperitoneal injection of salinomycin (5 mg/kg, an inhibitor of WNT/β-catenin signaling pathway) was evaluated by observing the changes in intestinal inflammation and detecting the expressions of tight junction proteins.

RESULTS

In the coculture system, WNT2b overexpression in the fibroblasts significantly promoted nuclear entry of β-catenin (P < 0.01) and decreased the expressions of tight junction proteins in Caco-2 cells; knockdown of FZD4 expression in Caco-2 cells obviously reversed this effect. In DSS-treated mice, salinomycin treatment significantly reduced intestinal inflammation and increased the expressions of tight junction proteins in the intestinal mucosa.

CONCLUSION

Intestinal fibroblasts overexpressing WNT2b causes impairment of intestinal mucosal barrier function and can be a potential target for treatment of IBD.

Model experiment research on HPTL anchoring technology for coal-rock composite roof in deep roadway

Since the western region of China, which is typical of extraordinary resource endowments, has gradually emerged as the major mining zone in China, the mining of thick coal seams and roadways with coal-rock composite roof have become more and more common in this region. However, it is extremely difficult to realize safe and effective maintenance and control of such roadways due to the differences in natural endowments of coal-rock masses. With the roadway with coal-rock composite roof of Hulusu Coal Mine in western China as the engineering background, experiment research on large-scale similarity model was conducted through comprehensive measures such as the pneumatic loading system, the surrounding rock stress monitoring system, the roadway deformation monitoring system, the bolt load monitoring system, and the displacement field monitoring system in this paper. According to the results of the experiment, the control effects of the three support systems on the roadway with coal-rock composite roof were significantly different. When the single support of short anchor bolts was applied, the comparatively low initial anchor-hold failed to constrain the initial micro deformation of the roof. Consequently, wide-range fractures of the roof were triggered at a loading pressure of 0.8 MPa. In the meanwhile, the deep surrounding rocks witnessed a downward inflection point in stress, accompanied by the possibility of the collapse of the thin-layer anchorage zone at any time. As for the support combining both short anchor bolts and long anchor cables, though a reinforced effect on the bolt anchorage zone could be achieved with the help of the cables, the active reinforcement capacity of the bolt was limited. The bolt anchorage zone was the first to be damaged at a loading pressure of 0.9 MPa, which would subsequently affect the effective bearing capacity of the deep surrounding rocks. In the application of the single support of high-strength long anchor bolts, the long bolts with high pre-tightening force were able to lock multiple groups of coal-rock strata to form a thick-layer anchorage bearing structure capable of withstanding a load as high as 1.0 MPa. The crash and collapse of the coal wall eventually caused the subsidence of the roof. Based on the intense dynamic load experiment and the feedbacks of engineering application outcomes in the field, it was concluded that the high-pretension thick-layer (HPTL) anchoring technology can effectively constrain the deformation of roadways with coal-rock composite roof with favorable application outcomes.

Uniaxial cyclic stretch enhances osteogenic differentiation of OPLL-derived primary cells via YAP-Wnt/β-catenin axis

The pathogenesis of posterior longitudinal ligament ossification (OPLL) remains inadequately understood. Mechanical stimulation is one of the important pathogenic factors in OPLL. As one of the mechanical stimulation transduction signals, the yes-associated protein (YAP) interacts with the Wnt/β-catenin signalling pathway, which plays an important role in osteogenic differentiation. This study aimed to demonstrate the role of YAP-Wnt/β-catenin axis in cell differentiation induced by mechanical stress. Primary cells extracted from posterior longitudinal ligament tissues from OPLL or non-OPLL patients were subjected to sinusoidal uniaxial cyclic stretch (5 %, 0.5 Hz, 3 d). The expression of runt-related transcription factor 2, collagen I, osterix, osteocalcin and alkaline phosphatase were compared between the static and the experimental groups. In addition, the cytoskeleton was detected using phalloidin staining while YAP phosphorylation states and nuclear location were identified using immunofluorescence. The results showed that mechanical stretching loading increased the expression of osteogenic genes and proteins in the OPLL group, while it had no significant effect on the control group. When OPLL cells were stretched, YAP exhibited an obvious nuclear translocation and the Wnt/β-catenin pathway was activated. Knocking down YAP or β-catenin could weaken the impact upon osteogenic differentiation induced by mechanical stimulation. YAP-mediated mechanical stimulation promoted osteogenic differentiation of OPLL cells through Wnt/β-catenin pathway and this progress was independent of the Hippo pathway.

The J-shape Association between Total Bilirubin and Stroke in Older Patients with Obstructive Sleep Apnea Syndrome: A Multicenter Study

OBJECTIVES

To explore the relationship between total bilirubin (TBil) and stroke risk in older patients with obstructive sleep apnea syndrome (OSAS).

METHODS

A total of 1,007 patients with OSAS without stroke history aged ≥ 60 years and with complete serum TBil records were enrolled in this study. The median follow-up was 42 months. Participants were divided into four groups based on the quartile of the baseline serum TBil concentration. Multivariate Cox proportional hazards analysis and restricted cubic spline (RCS) were used to investigate the association of TBil with the incidence of new-onset stroke.

RESULTS

The PRIMARY part: the third quantile TBil level group had the lowest prevalence of stroke among the four groups. The RCS functions depicted a J-type curve relationship between TBil (3.3-33.3 µmol/L) and stroke (nonlinear P < 0.05). When the TBil level was in the range of 3.3 to 11.5 µmol/L, the possible protective influence of bilirubin against stroke in patients with OSAS enhanced with an increasing TBil level. However, when the TBil level exceeded 11.5 µmol/L and gradually increased, the effect of TBil on stroke risk became more and more pronounced. The SECONDARY part: for every 1 µmol/L increase in TBil levels in the range of 11.5 to 33.3 µmol/L, the risk of stroke in patients with OSAS increased by 16.2% (P < 0.001). In addition, there was a higher risk in women with OSAS (hazard ratio (HR)=1.292, 95% confidence interval (95%CI): 1.093-1.528; P = 0.003). Moreover, an increased TBil level alone was significantly associated with stroke in subjects aged < 75 years (HR: 1.190, 95%CI: 1.069-1.324), patients with mild-to-moderate OSAS (HR: 1.215, 95%CI: 1.083-1.364), and individuals without atrial fibrillation (AF) (HR: 1.179, 95%CI: 1.083-1.285) within a TBil level in the range of 11.5 to 33.3 µmol/L.

CONCLUSIONS

Both lower and higher bilirubin levels may increase the risk of stroke in older persons with OSAS, and there was a J-type dose-response relationship. The risk of stroke was lowest when the TBil level was approximately 11.5 µmol/L.

Molecular Dynamics Simulations of Rhodamine B Zwitterion Diffusion in Polyelectrolyte Solutions

Polyelectrolytes continue to find wide interest and application in science and engineering, including areas such as water purification, drug delivery, and multilayer thin films. We have been interested in the dynamics of small molecules in a variety of polyelectrolyte (PE) environments; in this paper, we report simulations and analysis of the small dye molecule rhodamine B (RB) in several very simple polyelectrolyte solutions. Translational diffusion of the RB zwitterion has been measured in fully atomistic, 2 μs long molecular dynamics simulations in four different polyelectrolyte solutions. Two solutions contain the common polyanion sodium poly(styrene sulfonate) (PSS), one with a 30-mer chain and the other with 10 trimers. The other two solutions contain the common polycation poly(allyldimethylammonium) chloride (PDDA), one with two 15-mers and the other with 10 trimers. RB diffusion was also simulated in several polymer-free solutions to verify its known experimental value for the translational diffusion coefficient, D_RB, of 4.7 × 10^-6 cm²/s at 300 K. RB diffusion was slowed in all four simulated PE solutions, but to varying degrees. D_RB values of 3.07 × 10^-6 and 3.22 × 10^-6 cm²/s were found in PSS 30-mer and PSS trimer solutions, respectively, whereas PDDA 15-mer and trimer solutions yielded values of 2.19 × 10^-6 and 3.34 × 10^-6 cm²/s. Significant associations between RB and the PEs were analyzed and interpreted via a two-state diffusion model (bound and free diffusion) that describes the data well. Crowder size effects and anomalous diffusion were also analyzed. Finally, RB translation along the polyelectrolytes during association was characterized.

Advances in Anti-metabolic Disease Treatments Targeting CD47

Metabolic disorders include a cluster of conditions that result from hyperglycemia, hyperlipidemia, insulin resistance, obesity, and hepatic steatosis, which cause the dysfunction of immune cells and innate cells, such as macrophages, natural killer cells, vascular endothelial cells, hepatocytes, and human kidney tubular epithelial cells. Besides targeting the derangements in lipid metabolism, therapeutic modulations to regulate abnormal responses in the immune system and innate cell dysfunctions may prove to be promising strategies in the management of metabolic diseases. In recent years, several targets have been explored for the CD47 molecule (CD47), a glycosylated protein, which was originally reported to transmit an anti-phagocytic signal known as "don't eat me" in the atherosclerotic environment, hindering the efferocytosis of immune cells and promoting arterial plaque accumulation. Subsequently, the role of CD47 has been explored in obesity, fatty liver, and lipotoxic nephropathy, and its utility as a therapeutic target has been investigated using anti-CD47 antibodies or inhibitors of the THBS1/CD47 axis and the CD47/SIRPα signaling pathway. This review summarizes the mechanisms of action of CD47 in different cell types during metabolic diseases and the clinical research progress to date, providing a reference for the comprehensive targeting of CD47 to treat metabolic diseases and the devising of potential improvements to possible side effects.

Using Twitter Data Analysis to Understand the Perceptions, Awareness, and Barriers to the Wide Use of Pre-Exposure Prophylaxis in the United States

User-generated social media posts such as tweets can provide insights about the public's perception, cognitive, and behavioral responses to health-related issues. Pre-Exposure Prophylaxis (PrEP) is one of the most effective ways to reduce the risk of HIV infection. However, its utilization is low in the US, especially among populations disproportionately affected by HIV such as the age group of under 24 years old. It is therefore important to understand the barriers to the wider use of PrEP in the US using social media posts. In this study, we collected tweets from Twitter about PrEP in the past 4 years to identify such barriers by first identifying tweets about personal discussions, and then performing textual analysis using word analysis, UMLS semantic type analysis, and topic modeling. We found that the public often discussed advocacy, risks/benefits, access, pricing, insurance coverage, legislation, stigma, health education, and prevention of HIV. This result is consistent with the literature and can help identify strategies for promoting the use of PrEP, especially among young adults.

Motivation to Engage in Aging Research: Are There Typologies and Predictors?

BACKGROUND AND OBJECTIVES

Study recruitment and retention of older adults in research studies is a major challenge. Enhancing understanding of individual differences in motivations to participate, and predictors of motivators, can serve the dual aims of facilitating the recruitment and retention of older adults, benefiting study validity, economy, and power.

RESEARCH DESIGN AND METHODS

Older adults (N = 472) past and potential participants were surveyed about motivations to participate in research, demographic, and individual difference measures (e.g., health status, cognitive difficulties). Latent class and clustering analyses explored motivation typologies, followed by regression models predicting individual motivators and typologies.

RESULTS

Older adults endorsed a diversity of research motivations, some of which could be predicted by individual difference measures (e.g., older participants were more motivated by the desire to learn new technology, participants without a college education were more motivated by financial compensation, and participants with greater self-reported cognitive problems were more likely to participate to gain cognitive benefit). Clustering analysis revealed 4 motivation typologies: brain health advocates, research helpers, fun seekers, and multiple motivation enthusiasts. Cognitive difficulties, age, employment status, and previous participation predicted membership in these categories.

DISCUSSION AND IMPLICATIONS

Results provide an understanding of different participant motivations beyond differences between younger and older adults and begin to identify different classes of older adults motivated to participate in research studies. Results can provide guidance for targeted recruitment and retention strategies based on individual differences in stated or predicted motivations.

Deep learning-based predictions of older adults' adherence to cognitive training to support training efficacy

As the population ages, the number of older adults experiencing mild cognitive impairment (MCI), Alzheimer's disease, and other forms of dementia will increase dramatically over the next few decades. Unfortunately, cognitive changes associated with these conditions threaten independence and quality of life. To address this, researchers have developed promising cognitive training interventions to help prevent or reverse cognitive decline and cognitive impairment. However, the promise of these interventions will not be realized unless older adults regularly engage with them over the long term, and like many health behaviors, adherence to cognitive training interventions can often be poor. To maximize training benefits, it would be useful to be able to predict when adherence lapses for each individual, so that support systems can be personalized to bolster adherence and intervention engagement at optimal time points. The current research uses data from a technology-based cognitive intervention study to recognize patterns in participants' adherence levels and predict their future adherence to the training program. We leveraged the feature learning capabilities of deep neural networks to predict patterns of adherence for a given participant, based on their past behavior. A separate, personalized model was trained for each participant to capture individualistic features of adherence. We posed the adherence prediction as a binary classification problem and exploited multivariate time series analysis using an adaptive window size for model training. Further, data augmentation techniques were used to overcome the challenge of limited training data and enhance the size of the dataset. To the best of our knowledge, this is the first research effort to use advanced machine learning techniques to predict older adults' daily adherence to cognitive training programs. Experimental evaluations corroborated the promise and potential of deep learning models for adherence prediction, which furnished highest mean F-scores of 75.5, 75.5, and 74.6% for the Convolution Neural Network (CNN), Long Short-Term Memory (LSTM) network, and CNN-LSTM models respectively.

Physiological and biochemical differences in diapause and non-diapause pupae of Sericinus montelus (Lepidoptera: Papilionidae)

The swallowtail butterfly, Sericinus montelus Gray, is endemic to East Asia, has high ornamental value but faces an increased risk of extinction. To understand the overwintering strategies of this species, the dynamic changes in supercooling point (SCP) and water and biochemical contents of diapause-destined and non-diapause S. montelus pupae were investigated. The SCP of laboratory-reared diapause pupae was as low as -26°C compared to -24°C in diapause pupae in the field. Although there was no significant difference in total water content between diapause-destined and non-diapause pupae, the free water of diapause-destined pupae was significantly lower, and the bound water was significantly higher, than that of non-diapause pupae. Lipid, glycogen, and protein contents of diapause-destined pupae showed a downward trend, whereas the total sugar content showed the opposite trend after pupation. The glycogen content decreased rapidly during the initial stage of pupation, whereas the lipid content decreased significantly after 30 days of pupation, suggesting that diapause-destined pupae deplete glycogen stores during the pre-diapause period and then switch to using lipids during the diapause maintenance phase. Trehalose levels in diapause-destined pupae increased significantly and remained high after pupation. Meanwhile, the trehalose content of overwintering pupae during the diapause maintenance period was significantly higher than that of diapause termination pupae in the field. These results suggest that trehalose is the main cryoprotectant for overwintering pupae. Thus, diapausing S. montelus pupae appear to be freeze avoidant, accumulate trehalose as a cryoprotectant, and reduce the free water content to decrease the SCP, enhancing their cold tolerance.