Specific patterns and potential risk factors to predict 3-year risk of death among non-cancer patients with advanced chronic kidney disease by machine learning.

Chronic kidney disease (CKD) is a major public health concern. But there are limited machine learning studies on non-cancer patients with advanced CKD, and the results of machine learning studies on cancer patients with CKD may not apply directly on non-cancer patients. We aimed to conduct a comprehensive investigation of risk factors for a 3-year risk of death among non-cancer advanced CKD patients with an estimated glomerular filtration rate < 60.0 mL/min/1.73m2 by several machine learning algorithms. In this retrospective cohort study, we collected data from in-hospital and emergency care patients from 2 hospitals in Taiwan from 2009 to 2019, including their international classification of disease at admission and laboratory data from the hospital's electronic medical records (EMRs). Several machine learning algorithms were used to analyze the potential impact and degree of influence of each factor on mortality and survival. Data from 2 hospitals in northern Taiwan were collected with 6565 enrolled patients. After data cleaning, 26 risk factors and approximately 3887 advanced CKD patients from Shuang Ho Hospital were used as the training set. The validation set contained 2299 patients from Taipei Medical University Hospital. Predictive variables, such as albumin, PT-INR, and age, were the top 3 significant risk factors with paramount influence on mortality prediction. In the receiver operating characteristic curve, the random forest had the highest values for accuracy above 0.80. MLP, and Adaboost had better performance on sensitivity and F1-score compared to other methods. Additionally, SVM with linear kernel function had the highest specificity of 0.9983, while its sensitivity and F1-score were poor. Logistic regression had the best performance, with an area under the curve of 0.8527. Evaluating Taiwanese advanced CKD patients' EMRs could provide physicians with a good approximation of the patients' 3-year risk of death by machine learning algorithms.

Siglec-15/sialic acid axis as a central glyco-immune checkpoint in breast cancer bone metastasis.

Immunotherapy is a promising approach for treating metastatic breast cancer (MBC), offering new possibilities for therapy. While checkpoint inhibitors have shown great progress in the treatment of metastatic breast cancer, their effectiveness in patients with bone metastases has been disappointing. This lack of efficacy seems to be specific to the bone environment, which exhibits immunosuppressive features. In this study, we elucidate the multiple roles of the sialic acid-binding Ig-like lectin (Siglec)-15/sialic acid glyco-immune checkpoint axis in the bone metastatic niche and explore potential therapeutic strategies targeting this glyco-immune checkpoint. Our research reveals that elevated levels of Siglec-15 in the bone metastatic niche can promote tumor-induced osteoclastogenesis as well as suppress antigen-specific T cell responses. Next, we demonstrate that antibody blockade of the Siglec-15/sialic acid glyco-immune checkpoint axis can act as a potential treatment for breast cancer bone metastasis. By targeting this pathway, we not only aim to treat bone metastasis but also inhibit the spread of metastatic cancer cells from bone lesions to other organs.

Rapid identification of full-length genome and tracing variations of monkeypox virus in clinical specimens based on mNGS and amplicon sequencing.

The monkeypox virus (MPXV) has triggered a current outbreak globally. Genome sequencing of MPXV and rapid tracing of genetic variants will benefit disease diagnosis and control. It is a significant challenge but necessary to optimize the strategy and application of rapid full-length genome identification and to track variations of MPXV in clinical specimens with low viral loads, as it is one of the DNA viruses with the largest genome and the most AT-biased, and has a significant number of tandem repeats. Here we evaluated the performance of metagenomic and amplicon sequencing techniques, and three sequencing platforms in MPXV genome sequencing based on multiple clinical specimens of five mpox cases in Chinese mainland. We rapidly identified the full-length genome of MPXV with the assembly of accurate tandem repeats in multiple clinical specimens. Amplicon sequencing enables cost-effective and rapid sequencing of clinical specimens to obtain high-quality MPXV genomes. Third-generation sequencing facilitates the assembly of the terminal tandem repeat regions in the monkeypox virus genome and corrects a common misassembly in published sequences. Besides, several intra-host single nucleotide variations were identified in the first imported mpox case. This study offers an evaluation of various strategies aimed at identifying the complete genome of MPXV in clinical specimens. The findings of this study will significantly enhance the surveillance of MPXV.

Exploring the Potential Performance of Fibroscan for Predicting and Evaluating Metabolic Syndrome using a Feature Selected Strategy of Machine Learning.

Metabolic syndrome (MetS) includes several conditions that can increase an individual's predisposition to high-risk cardiovascular events, morbidity, and mortality. Non-alcoholic fatty liver disease (NAFLD) is a predominant cause of cirrhosis, which is a global indicator of liver transplantation and is considered the hepatic manifestation of MetS. FibroScan® provides an accurate and non-invasive method for assessing liver steatosis and fibrosis in patients with NAFLD, via a controlled attenuation parameter (CAP) and liver stiffness measurement (LSM or E) scores and has been widely used in current clinical practice. Several machine learning (ML) models with a recursive feature elimination (RFE) algorithm were applied to evaluate the importance of the CAP score. Analysis by ANOVA revealed that five symptoms at different CAP and E score levels were significant. All eight ML models had accuracy scores > 0.9, while treebags and random forest had the best kappa values (0.6439 and 0.6533, respectively). The CAP score was the most important variable in the seven ML models. Machine learning models with RFE demonstrated that using the CAP score to identify patients with MetS may be feasible. Thus, a combination of CAP scores and other significant biomarkers could be used for early detection in predicting MetS.

Detecting SARS-CoV-2 BA.2, BA.4, and BA.5 Variants Utilizing a Robust RT-RPA-CRISPR/Cas12a-Based Method - China, 2023.

Introduction: Since 2019, numerous variants of concern for severe acute respiratory syndrome virus 2 (SARS-CoV-2) have emerged, leading to significant outbreaks. The development of novel, highly accurate, and rapid detection techniques for these new SARS-CoV-2 variants remains a primary focus in the ongoing efforts to control and prevent the coronavirus disease 2019 (COVID-19) pandemic. Methods: Reverse transcription-recombinase polymerase amplification combined with the clustered regularly interspaced short palindromic repeats-associated protein 12a (CRISPR/Cas12a) system was used to validate the detection of the Omicron BA.2, BA.4, and BA.5 variants of SARS-CoV-2. Results: Our results demonstrate that the CRISPR/Cas12a assay is capable of effectively detecting the SARS-CoV-2 BA.2, BA.4, and BA.5 variants with a limit of detection of 10, 1, and 10 copies/µL, respectively. Importantly, our assay successfully differentiated the three SARS-CoV-2 Omicron strains from one another. Additionally, we evaluated 46 SARS-CoV-2 positive clinical samples consisting of BA.2 (n=20), BA.4 (n=6), and BA.5 (n=20) variants, and the sensitivity of our assay ranged from 90% to 100%, while the specificity was 100%. Discussion: This research presents a swift and reliable CRISPR-based method that may be employed to track the emergence of novel SARS-CoV-2 variants.

Photostable Small-Molecule NIR-II Fluorescent Scaffolds that Cross the Blood-Brain Barrier for Noninvasive Brain Imaging.

The second near-infrared (NIR-II, 1000-1700 nm) fluorescent probes have significant advantages over visible or NIR-I (600-900 nm) imaging for both depth of penetration and level of resolution. Since the blood-brain barrier (BBB) prevents most molecules from entering the central nervous system, NIR-II dyes with large molecular frameworks have limited applications for brain imaging. In this work, we developed a series of boron difluoride (BF2) formazanate NIR-II dyes, which had tunable photophysical properties, ultrahigh photostability, excellent biological stability, and strong brightness. Modulation of the aniline moiety of BF2 formazanate dyes significantly enhances their abilities to cross the BBB for noninvasive brain imaging. Furthermore, the intact mouse brain imaging and dynamic dye diffusion across the BBB were monitored using these BF2 formazanate dyes in the NIR-II region. In murine glioblastoma models, these dyes can differentiate tumors from normal brain tissues. We anticipate that this new type of small molecule will find potential applications in creating probes and drugs relevant to theranostic for brain pathologies.

Development of two multiplex real-time PCR assays for simultaneous detection and differentiation of monkeypox virus IIa, IIb, and I clades and the B.1 lineage.

An ongoing multi-country outbreak of monkeypox was reported in May 2022 with several deaths, affecting 107 countries of all six World Health Organization (WHO) regions. The WHO has declared the current monkeypox outbreak to be a Public Health Emergency of International Concern. It is, thus, necessary to rapidly and accurately detect and distinguish different monkeypox virus (MPXV) clades. We designed primers and probes based on the alignment of 138 complete genomes of poxviruses. In Panel 1, we mixed one pair of primers and three probes to detect and differentiate the MPXV Western Africa (IIa, IIb clade) and Congo Basin (I clade) and other orthopoxviruses. In Panel 2, we mixed one pair of primers and two probes to detect the 2022 MPXV (B.1 lineage and its descendant lineages). In addition, we tested the specificity and sensitivity of the assay using real-time PCR. In Panel 1, the assay reproducibly identified various concentrations of two plasmids of the monkeypox virus, whereas other orthopoxviruses did not cross-react. In Panel 2, the probe annealed well to MPXV B.1 and showed the expected linearity. These two multiple real-time assays are inclusive and highly specific for identifying different clades of MPXV.

Expanding the eukaryotic genetic code with a biosynthesized 21st amino acid.

Genetic code expansion technology allows for the use of noncanonical amino acids (ncAAs) to create semisynthetic organisms for both biochemical and biomedical applications. However, exogenous feeding of chemically synthesized ncAAs at high concentrations is required to compensate for the inefficient cellular uptake and incorporation of these components into proteins, especially in the case of eukaryotic cells and multicellular organisms. To generate organisms capable of autonomously biosynthesizing an ncAA and incorporating it into proteins, we have engineered a metabolic pathway for the synthesis of O-methyltyrosine (OMeY). Specifically, we endowed organisms with a marformycins biosynthetic pathway-derived methyltransferase that efficiently converts tyrosine to OMeY in the presence of the co-factor S-adenosylmethionine. The resulting cells can produce and site-specifically incorporate OMeY into proteins at much higher levels than cells exogenously fed OMeY. To understand the structural basis for the substrate selectivity of the transferase, we solved the X-ray crystal structures of the ligand-free and tyrosine-bound enzymes. Most importantly, we have extended this OMeY biosynthetic system to both mammalian cells and the zebrafish model to enhance the utility of genetic code expansion. The creation of autonomous eukaryotes using a 21st amino acid will make genetic code expansion technology more applicable to multicellular organisms, providing valuable vertebrate models for biological and biomedical research.

Unleashing the potential of noncanonical amino acid biosynthesis to create cells with precision tyrosine sulfation.

Despite the great promise of genetic code expansion technology to modulate structures and functions of proteins, external addition of ncAAs is required in most cases and it often limits the utility of genetic code expansion technology, especially to noncanonical amino acids (ncAAs) with poor membrane internalization. Here, we report the creation of autonomous cells, both prokaryotic and eukaryotic, with the ability to biosynthesize and genetically encode sulfotyrosine (sTyr), an important protein post-translational modification with low membrane permeability. These engineered cells can produce site-specifically sulfated proteins at a higher yield than cells fed exogenously with the highest level of sTyr reported in the literature. We use these autonomous cells to prepare highly potent thrombin inhibitors with site-specific sulfation. By enhancing ncAA incorporation efficiency, this added ability of cells to biosynthesize ncAAs and genetically incorporate them into proteins greatly extends the utility of genetic code expansion methods.

[Using Social Prescribing to Practice Social Responsibility: A Case Study in the Taipei Medical University System].

The Ministry of Education launched the University Social Responsibility (USR) Program in 2018. Since then, universities have actively promoted inter-disciplinary cooperation and implemented high-end knowledge to meet community needs. Universities are using social responsibility to enhance the level of social participation engaged in by their students to achieve the sustainable development goals set by the United Nations. The aim of this paper was to share the experience of the Taipei Medical University (TMU) system in practicing social responsibility by integrating TMU resources with those of TMU-affiliated hospitals. The USR program at Taipei Medical University promotes the reform of school governance through encouraging university faculties to collaborate with hospital physicians to develop a specific curriculum that implements an innovative social-prescribing model. This curriculum is designed to provide opportunities for students to step out the classroom and into the community. Through clinical observations, home visits, and community service, students gain a deep understanding of community health issues from residents in the surrounding neighborhoods. Medical humanities education is achieved through students' involvement in both patient individual care and community health issues. In addition, faculties guide students in reflective learning from holistic healthcare perspectives. Students are encouraged to use evidence-based methods to develop innovative models of care in the community. Medical staff participation in this program helps ensure that social prescribing to community residents accurately reflects professional assessments. These prescriptions refer patients to local health promotion units involved in community collaboration. The medical university students build a bridge between the medical system and the community to implement the goals of health education. The impact of social prescribing on the social determinants of health is known to be significantly greater than that of medicine prescriptions. The expected outcomes of this project are to reduce the health inequalities experienced by vulnerable groups in the community and to share Taiwan's experiences with the academic community worldwide.

Bone-Specific Enhancement of Antibody Therapy for Breast Cancer Metastasis to Bone.

Despite the rapid evolution of therapeutic antibodies, their clinical efficacy in the treatment of bone tumors is hampered due to the inadequate pharmacokinetics and poor bone tissue accessibility of these large macromolecules. Here, we show that engineering therapeutic antibodies with bone-homing peptide sequences dramatically enhances their concentrations in the bone metastatic niche, resulting in significantly reduced survival and progression of breast cancer bone metastases. To enhance the bone tumor-targeting ability of engineered antibodies, we introduced varying numbers of bone-homing peptides into permissive sites of the anti-HER2 antibody, trastuzumab. Compared to the unmodified antibody, the engineered antibodies have similar pharmacokinetics and in vitro cytotoxic activity, but exhibit improved bone tumor distribution in vivo. Accordingly, in xenograft models of breast cancer metastasis to bone sites, engineered antibodies with enhanced bone specificity exhibit increased inhibition of both initial bone metastases and secondary multiorgan metastases. Furthermore, this engineering strategy is also applied to prepare bone-targeting antibody-drug conjugates with enhanced therapeutic efficacy. These results demonstrate that adding bone-specific targeting to antibody therapy results in robust bone tumor delivery efficacy. This provides a powerful strategy to overcome the poor accessibility of antibodies to the bone tumors and the consequential resistance to the therapy.

Biosynthesis and Genetic Incorporation of 3,4-Dihydroxy-L-Phenylalanine into Proteins in Escherichia coli.

While 20 canonical amino acids are used by most organisms for protein synthesis, the creation of cells that can use noncanonical amino acids (ncAAs) as additional protein building blocks holds great promise for preparing novel medicines and for studying complex questions in biological systems. However, only a small number of biosynthetic pathways for ncAAs have been reported to date, greatly restricting our ability to generate cells with ncAA building blocks. In this study, we report the creation of a completely autonomous bacterium that utilizes 3,4-dihydroxy-L-phenylalanine (DOPA) as its 21st amino acid building block. Like canonical amino acids, DOPA can be biosynthesized without exogenous addition and can be genetically incorporated into proteins in a site-specific manner. Equally important, the protein production yields of DOPA-containing proteins from these autonomous cells are greater than those from cells exogenously fed with 9 mM DOPA. The unique catechol moiety of DOPA can be used as a versatile handle for site-specific protein functionalizations via either oxidative coupling or strain-promoted oxidation-controlled cyclooctyne-1,2-quinone (SPOCQ) cycloaddition reactions. We further demonstrate the use of these autonomous cells in preparing fluorophore-labeled anti-human epidermal growth factor 2 (HER2) antibodies for the detection of HER2 expression on cancer cells.

Harnessing the power of antibodies to fight bone metastasis.

Antibody-based therapies have proved to be of great value in cancer treatment. Despite the clinical success of these biopharmaceuticals, reaching targets in the bone microenvironment has proved to be difficult due to the relatively low vascularization of bone tissue and the presence of physical barriers. Here, we have used an innovative bone-targeting (BonTarg) technology to generate a first-in-class bone-targeting antibody. Our strategy involves the use of pClick antibody conjugation technology to chemically couple the bone-targeting moiety bisphosphonate to therapeutic antibodies. Bisphosphonate modification of these antibodies results in the delivery of higher conjugate concentrations to the bone metastatic niche, relative to other tissues. In xenograft mice models, this strategy provides enhanced inhibition of bone metastases and multiorgan secondary metastases that arise from bone lesions. Specific delivery of therapeutic antibodies to the bone, therefore, represents a promising strategy for the treatment of bone metastatic cancers and other bone diseases.

Exploring and predicting mortality among patients with end-stage liver disease without cancer: a machine learning approach.

OBJECTIVE: End-stage liver disease is a global public health problem with a high mortality rate. Early identification of people at risk of poor prognosis is fundamental for decision-making in clinical settings. This study created a machine learning prediction system that provides several related models with visualized graphs, including decision trees, ensemble learning and clustering, to predict mortality in patients with end-stage liver disease. METHODS: A retrospective cohort study was conducted: the training data were from patients enrolled from January 2009 to December 2010 and followed up to December 2014; validation data were from patients enrolled from January 2015 to December 2016 and followed up to January 2019. Hospitalized patients with noncancer-related chronic liver disease were identified from the hospital's electrical medical records. RESULTS: In traditional multivariable logistic regression and Cox proportional hazard model, prothrombin time of international normalized ratio, which was significant with P value = 0.002, odds ratio = 2.790 and hazard ratio 1.363. Besides, blood urea nitrogen and C-reactive protein were also significant, with P value <0.001 and 0.026. The area under the curve was 0.771 in the receiver operating characteristic curve. In machine learning, blood urea nitrogen and age were regarded as the primary factors for predicting mortality. Creatinine, prothrombin time of international normalized ratio and bilirubin were also significant mortality predictors. The area under the curve of the random forest and AdaBoost was 0.838 and 0.792. CONCLUSION: The machine learning techniques provided a comprehensive assessment of patient conditions; it could help physicians make an accurate diagnosis of chronic liver disease and improve healthcare management.

Site-Specific Incorporation of a Photoactivatable Fluorescent Amino Acid.

Photoactivatable fluorophores are emerging optical probes for biological applications. Most photoactivatable fluorophores are relatively large in size and need to be activated by ultraviolet light; this dramatically limits their applications. To introduce photoactivatable fluorophores into proteins, recent investigations have explored several protein-labeling technologies, including fluorescein arsenical hairpin (FlAsH) Tag, HaloTag labeling, SNAPTag labeling, and other bioorthogonal chemistry-based methods. However, these technologies require a multistep labeling process. Here, by using genetic code expansion and a single sulfur-for-oxygen atom replacement within an existing fluorescent amino acid, we have site-specifically incorporated the photoactivatable fluorescent amino acid thioacridonylalanine (SAcd) into proteins in a single step. Moreover, upon exposure to visible light, SAcd can be efficiently desulfurized to its oxo derivatives, thus restoring the strong fluorescence of labeled proteins.

Creation of Bacterial cells with 5-Hydroxytryptophan as a 21st Amino Acid Building Block.

While most organisms utilize 20 canonical amino acid building blocks for protein synthesis, adding additional candidates to the amino acid repertoire can greatly facilitate the investigation and manipulation of protein structures and functions. In this study, we report the generation of completely autonomous organisms with a 21st ncAA, 5-hydroxytryptophan (5HTP). Like 20 canonical amino acids, 5-hydroxytryptophan can be biosynthesized in vivo from simple carbon sources and is subsequently incorporated into proteins in response to the amber stop codon. Using this unnatural organism, we have prepared a single-chain immunoglobulin variable fragment conjugated with a fluorophore and demonstrated the utility of these autonomous cells to monitor oxidative stress. Creation of this and other cells containing the 21st amino acid will provide an opportunity to generate proteins and organisms with novel activities, as well as to determine the evolutionary consequences of using additional amino acid buildings.

Addition of Isocyanide-Containing Amino Acids to the Genetic Code for Protein Labeling and Activation.

Site-specific introduction of bioorthogonal handles into biomolecules provides powerful tools for studying and manipulating the structures and functions of proteins. Recent advances in bioorthogonal chemistry demonstrate that tetrazine-based bioorthogonal cycloaddition is a particularly useful methodology due to its high reactivity, biological selectivity, and turn-on property for fluorescence imaging. Despite its broad applications in protein labeling and imaging, utilization of tetrazine-based bioorthogonal cycloaddition has been limited to date by the requirement of a hydrophobic strained alkene reactive moiety. Circumventing this structural requirement, we report the site-specific incorporation of noncanonical amino acids (ncAAs) with a small isocyanide (or isonitrile) group into proteins in both bacterial and mammalian cells. We showed that under physiological conditions and in the absence of a catalyst these isocyanide-containing ncAAs could react selectively with tetrazine molecules via [4 + 1]-cycloaddition, thus providing a versatile bioorthogonal handle for site-specific protein labeling and protein decaging. Significantly, these bioorthogonal reactions between isocyanides and tetrazines also provide a unique mechanism for the activation of tetrazine-quenched fluorophores. The addition of these isocyanide-containing ncAAs to the list of 20 commonly used, naturally occurring amino acids expands our repertoire of reagents for bioorthogonal chemistry, therefore enabling new biological applications ranging from protein labeling and imaging studies to the chemical activation of proteins.

Self-Sterilizing Laser-Induced Graphene Bacterial Air Filter.

Nosocomial infections transmitted through airborne, droplet, aerosol, and particulate-transported modes pose substantial infection risks to patients and healthcare employees. In this study, we demonstrate a self-cleaning filter comprised of laser-induced graphene (LIG), a porous conductive graphene foam formed through photothermal conversion of a polyimide film by a commercial CO2 laser cutter. LIG was shown to capture particulates and bacteria. The bacteria cannot proliferate even when submerged in culture medium. Through a periodic Joule-heating mechanism, the filter readily reaches >300 °C. This destroys any microorganisms including bacteria, along with molecules that can cause adverse biological reactions and diseases. These molecules include pyrogens, allergens, exotoxins, endotoxins, mycotoxins, nucleic acids, and prions. Capitalizing on the high surface area and thermal stability of LIG, the utility of graphene for reduction of nosocomial infection in hospital settings is suggested.