Natural determinant reference functional theory.

The natural determinant reference (NDR) or principal natural determinant is the Slater determinant comprised of the N most strongly occupied natural orbitals of an N-electron state of interest. Unlike the Kohn-Sham (KS) determinant, which yields the exact ground-state density, the NDR only yields the best idempotent approximation to the interacting one-particle reduced density matrix, but it is well-defined in common atom-centered basis sets and is representation-invariant. We show that the under-determination problem of prior attempts to define a ground-state energy functional of the NDR is overcome in a grand-canonical ensemble framework at the zero-temperature limit. The resulting grand potential functional of the NDR ensemble affords the variational determination of the ground state energy, its NDR (ensemble), and select ionization potentials and electron affinities. The NDR functional theory can be viewed as an "exactification" of orbital optimization and empirical generalized KS methods. NDR functionals depending on the noninteracting Hamiltonian do not require troublesome KS-inversion or optimized effective potentials.

Re-engineering a Clinical Trial Management System Using Blockchain Technology: System Design, Development, and Case Studies.

BACKGROUND: A clinical trial management system (CTMS) is a suite of specialized productivity tools that manage clinical trial processes from study planning to closeout. Using CTMSs has shown remarkable benefits in delivering efficient, auditable, and visualizable clinical trials. However, the current CTMS market is fragmented, and most CTMSs fail to meet expectations because of their inability to support key functions, such as inconsistencies in data captured across multiple sites. Blockchain technology, an emerging distributed ledger technology, is considered to potentially provide a holistic solution to current CTMS challenges by using its unique features, such as transparency, traceability, immutability, and security. OBJECTIVE: This study aimed to re-engineer the traditional CTMS by leveraging the unique properties of blockchain technology to create a secure, auditable, efficient, and generalizable CTMS. METHODS: A comprehensive, blockchain-based CTMS that spans all stages of clinical trials, including a sharable trial master file system; a fast recruitment and simplified enrollment system; a timely, secure, and consistent electronic data capture system; a reproducible data analytics system; and an efficient, traceable payment and reimbursement system, was designed and implemented using the Quorum blockchain. Compared with traditional blockchain technologies, such as Ethereum, Quorum blockchain offers higher transaction throughput and lowers transaction latency. Case studies on each application of the CTMS were conducted to assess the feasibility, scalability, stability, and efficiency of the proposed blockchain-based CTMS. RESULTS: A total of 21.6 million electronic data capture transactions were generated and successfully processed through blockchain, with an average of 335.4 transactions per second. Of the 6000 patients, 1145 were matched in 1.39 seconds using 10 recruitment criteria with an automated matching mechanism implemented by the smart contract. Key features, such as immutability, traceability, and stability, were also tested and empirically proven through case studies. CONCLUSIONS: This study proposed a comprehensive blockchain-based CTMS that covers all stages of the clinical trial process. Compared with our previous research, the proposed system showed an overall better performance. Our system design, implementation, and case studies demonstrated the potential of blockchain technology as a potential solution to CTMS challenges and its ability to perform more health care tasks.

A novel miRNA-based classification model of risks and stages for clear cell renal cell carcinoma patients.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal carcinoma and patients at advanced stage showed poor survival rate. Despite microRNAs (miRNAs) are used as potential biomarkers in many cancers, miRNA biomarkers for predicting the tumor stage of ccRCC are still limitedly identified. Therefore, we proposed a new integrated machine learning (ML) strategy to identify a novel miRNA signature related to tumor stage and prognosis of ccRCC patients using miRNA expression profiles. A multivariate Cox regression model with three hybrid penalties including Least absolute shrinkage and selection operator (Lasso), Adaptive lasso and Elastic net algorithms was used to screen relevant prognostic related miRNAs. The best subset regression (BSR) model was used to identify optimal prognostic model. Five ML algorithms were used to develop stage classification models. The biological significance of the miRNA signature was analyzed by utilizing DIANA-mirPath. RESULTS: A four-miRNA signature associated with survival was identified and the expression of this signature was strongly correlated with high risk patients. The high risk patients had unfavorable overall survival compared with the low risk group (HR = 4.523, P-value = 2.86e-08). Univariate and multivariate analyses confirmed independent and translational value of this predictive model. A combined ML algorithm identified six miRNA signatures for cancer staging prediction. After using the data balancing algorithm SMOTE, the Support Vector Machine (SVM) algorithm achieved the best classification performance (accuracy = 0.923, sensitivity = 0.927, specificity = 0.919, MCC = 0.843) when compared with other classifiers. Furthermore, enrichment analysis indicated that the identified miRNA signature involved in cancer-associated pathways. CONCLUSIONS: A novel miRNA classification model using the identified prognostic and tumor stage associated miRNA signature will be useful for risk and stage stratification for clinical practice, and the identified miRNA signature can provide promising insight to understand the progression mechanism of ccRCC.

Selfconsistent random phase approximation methods.

This Perspective reviews recent efforts toward selfconsistent calculations of ground-state energies within the random phase approximation (RPA) in the (generalized) Kohn-Sham (KS) density functional theory context. Since the RPA correlation energy explicitly depends on the non-interacting KS potential, an additional condition to determine the energy as a functional of the density is necessary. This observation leads to the concept of functional selfconsistency (FSC), which requires that the KS density equals the interacting density defined as the functional derivative of the ground-state energy with respect to the external potential. While all existing selfconsistent RPA schemes violate FSC, the recent generalized KS semicanonical projected RPA (GKS-spRPA) method takes a step toward satisfying it. This leads to systematic improvements in densities, binding energy curves, reference state stability, and molecular properties compared to non-selfconsistent RPA as well as optimized effective potential RPA. GKS-spRPA orbital energies accurately approximate valence and core ionization potentials, and even electron affinities of non-valence bound anions. The computational cost and performance of GKS-spRPA are compared to those of related selfconsistent schemes, including GW and orbital optimization methods, and limitations are discussed. Large differences between KS and interacting densities observed in the absence of FSC and the well-rounded performance of GKS-spRPA suggest that the KS potential as a density functional should be defined via the FSC condition for explicitly potential-dependent density functionals.

Construction and Validation of a Prognostic Gene-Based Model for Overall Survival Prediction in Hepatocellular Carcinoma Using an Integrated Statistical and Bioinformatic Approach.

Hepatocellular carcinoma (HCC) is one of the most common lethal cancers worldwide and is often related to late diagnosis and poor survival outcome. More evidence is demonstrating that gene-based prognostic models can be used to predict high-risk HCC patients. Therefore, our study aimed to construct a novel prognostic model for predicting the prognosis of HCC patients. We used multivariate Cox regression model with three hybrid penalties approach including least absolute shrinkage and selection operator (Lasso), adaptive lasso and elastic net algorithms for informative prognostic-related genes selection. Then, the best subset regression was used to identify the best prognostic gene signature. The prognostic gene-based risk score was constructed using the Cox coefficient of the prognostic gene signature. The model was evaluated by Kaplan-Meier (KM) and receiver operating characteristic curve (ROC) analyses. A novel four-gene signature associated with prognosis was identified and the risk score was constructed based on the four-gene signature. The risk score efficiently distinguished the patients into a high-risk group with poor prognosis. The time-dependent ROC analysis revealed that the risk model had a good performance with an area under the curve (AUC) of 0.780, 0.732, 0.733 in 1-, 2- and 3-year prognosis prediction in The Cancer Genome Atlas (TCGA) dataset. Moreover, the risk score revealed a high diagnostic performance to classify HCC from normal samples. The prognosis and diagnosis prediction performances of risk scores were verified in external validation datasets. Functional enrichment analysis of the four-gene signature and its co-expressed genes involved in the metabolic and cell cycle pathways was constructed. Overall, we developed a novel-gene-based prognostic model to predict high-risk HCC patients and we hope that our findings can provide promising insight to explore the role of the four-gene signature in HCC patients and aid risk classification.

Text mining in a literature review of urothelial cancer using topic model.

BACKGROUND: Urothelial cancer (UC) includes carcinomas of the bladder, ureters, and renal pelvis. New treatments and biomarkers of UC emerged in this decade. To identify the key information in a vast amount of literature can be challenging. In this study, we use text mining to explore UC publications to identify important information that may lead to new research directions. METHOD: We used topic modeling to analyze the titles and abstracts of 29,883 articles of UC from Pubmed, Web of Science, and Embase in Mar 2020. We applied latent Dirichlet allocation modeling to extract 15 topics and conducted trend analysis. Gene ontology term enrichment analysis and Kyoto encyclopedia of genes and genomes pathway analysis were performed to identify UC related pathways. RESULTS: There was a growing trend regarding UC treatment especially immune checkpoint therapy but not the staging of UC. The risk factors of UC carried in different countries such as cigarette smoking in the United State and aristolochic acid in Taiwan and China. GMCSF, IL-5, Syndecan-1, ErbB receptor, integrin, c-Met, and TRAIL signaling pathways are the most relevant biological pathway associated with UC. CONCLUSIONS: The risk factors of UC may be dependent on the countries and GMCSF, IL-5, Syndecan-1, ErbB receptor, integrin, c-Met, and TRAIL signaling pathways are the most relevant biological pathway associated with UC. These findings may provide further UC research directions.

Identification of most influential co-occurring gene suites for gastrointestinal cancer using biomedical literature mining and graph-based influence maximization.

BACKGROUND: Gastrointestinal (GI) cancer including colorectal cancer, gastric cancer, pancreatic cancer, etc., are among the most frequent malignancies diagnosed annually and represent a major public health problem worldwide. METHODS: This paper reports an aided curation pipeline to identify potential influential genes for gastrointestinal cancer. The curation pipeline integrates biomedical literature to identify named entities by Bi-LSTM-CNN-CRF methods. The entities and their associations can be used to construct a graph, and from which we can compute the sets of co-occurring genes that are the most influential based on an influence maximization algorithm. RESULTS: The sets of co-occurring genes that are the most influential that we discover include RARA - CRBP1, CASP3 - BCL2, BCL2 - CASP3 - CRBP1, RARA - CASP3 - CRBP1, FOXJ1 - RASSF3 - ESR1, FOXJ1 - RASSF1A - ESR1, FOXJ1 - RASSF1A - TNFAIP8 - ESR1. With TCGA and functional and pathway enrichment analysis, we prove the proposed approach works well in the context of gastrointestinal cancer. CONCLUSIONS: Our pipeline that uses text mining to identify objects and relationships to construct a graph and uses graph-based influence maximization to discover the most influential co-occurring genes presents a viable direction to assist knowledge discovery for clinical applications.

Usefulness of Therapeutic Hypothermia to Improve Survival in Out-of-Hospital Cardiac Arrest.

BACKGROUND: In recent years, therapeutic hypothermia (TH) has been used to improve outcomes in patients with out-of-hospital cardiac arrest (OHCA). Despite these recommendations, many centers are still hesitant to implement such hypothermia protocols. In this study, we assessed the effects of TH for OHCA patients. METHODS: A total of 58 OHCA patients who had return of spontaneous circulation after OHCA presumed to be due to cardiac causes were enrolled. Twenty-three patients underwent TH, which was performed using a large volume of ice crystalloid fluid infusions in the emergency room and conventional cooling blankets in the ICU to maintain a body temperature of 32-34 °C for 24 hours using a tympanic thermometer. Patients in the control group received standard supportive care without TH. Hospital survival and neurologic outcomes were compared. RESULTS: There were no significant differences between the groups in patient characteristics, underlying etiologies and disease severity. In the 23 patients who received TH, 17 were alive at hospital discharge. In the 35 patients who received supportive care, only 11 were alive at hospital discharge (73.91% vs. 31.43%, p = 0.0015). Approximately 52% of the patients in the TH group had good neurologic outcomes (12 of 23) compared with the 20% (7 of 35) of the patients in the supportive group (p = 0.01). CONCLUSIONS: TH can improve the outcomes of OHCA patients. Further large-scale studies are needed to verify our results.

Attention to Multiple Objects Facilitates Their Integration in Prefrontal and Parietal Cortex.

Selective attention is known to interact with perceptual organization. In visual scenes, individual objects that are distinct and discriminable may occur on their own, or in groups such as a stack of books. The main objective of this study is to probe the neural interaction that occurs between individual objects when attention is directed toward one or more objects. Here we record steady-state visual evoked potentials via electrocorticography to directly assess the responses to individual stimuli and to their interaction. When human participants attend to two adjacent stimuli, prefrontal and parietal cortex shows a selective enhancement of only the neural interaction between stimuli, but not the responses to individual stimuli. When only one stimulus is attended, the neural response to that stimulus is selectively enhanced in prefrontal and parietal cortex. In contrast, early visual areas generally manifest responses to individual stimuli and to their interaction regardless of attentional task, although a subset of the responses is modulated similarly to prefrontal and parietal cortex. Thus, the neural representation of the visual scene as one progresses up the cortical hierarchy becomes more highly task-specific and represents either individual stimuli or their interaction, depending on the behavioral goal. Attention to multiple objects facilitates an integration of objects akin to perceptual grouping.SIGNIFICANCE STATEMENT Individual objects in a visual scene are seen as distinct entities or as parts of a whole. Here we examine how attention to multiple objects affects their neural representation. Previous studies measured single-cell or fMRI responses and obtained only aggregate measures that combined the activity to individual stimuli as well as their potential interaction. Here, we directly measure electrocorticographic steady-state responses corresponding to individual objects and to their interaction using a frequency-tagging technique. Attention to two stimuli increases the interaction component that is a hallmark for perceptual integration of stimuli. Furthermore, this stimulus-specific interaction is represented in prefrontal and parietal cortex in a task-dependent manner.

Parapharyngeal Schwannoma of the Mandibular Nerve Associated With Auditory Changes.

We present a case of a parapharyngeal schwannoma of the mandibular nerve with intraosseous extension into the mandible. The initial symptoms included decreased auditory acuity, with subsequent magnetic resonance imaging findings suggestive of Eustachian tube obstruction. This represents a rare symptom of schwannomas of the mandibular nerve. Owing to the degree of bony expansion and cortical thinning of the adjacent mandibular ramus, concern existed for a pathologic fracture. Treatment involved complete excision of the lesion using hemimandibulectomy with second stage reconstruction. The patient noted resolution of the preoperative symptoms. No sign of recurrence of the schwannoma was noted at the 2-year mark.

Fibrous Dysplasia and Medication-Related Osteonecrosis of the Jaw.

PURPOSE: Osteonecrosis of the jaw (ONJ) is an established side effect of intravenous bisphosphonates and other antiresorptive medications. Although bisphosphonates are frequently prescribed for patients with the skeletal disorder fibrous dysplasia (FD), there are no reports of ONJ in this population. This has led some to conclude that patients with FD are at low risk for the development of bisphosphonate-related ONJ. PATIENTS AND METHODS: Patients were evaluated as part of a longstanding FD natural history study at the National Institutes of Health. RESULTS: Of 76 patients with FD who were treated with bisphosphonates, 4 developed ONJ (5.4%). Three patients developed ONJ in areas of FD-affected bone and 1 in an area of normal bone. All 4 patients had features known to be associated with ONJ in the general population, including long-term high-dose intravenous bisphosphonate treatment, periodontal and endodontic infections, and dentoalveolar surgical procedures. CONCLUSIONS: These cases establish ONJ as a potential complication of bisphosphonate treatment in patients with FD. The presence of established risk factors for ONJ in this group of patients with FD suggests that high-risk patients could be identified before the development of ONJ. Clinicians should use caution in prescribing bisphosphonates to patients with FD and should do so only for established indications.

Finding a Potential Dipeptidyl Peptidase-4 (DPP-4) Inhibitor for Type-2 Diabetes Treatment Based on Molecular Docking, Pharmacophore Generation, and Molecular Dynamics Simulation.

Dipeptidyl peptidase-4 (DPP-4) is the vital enzyme that is responsible for inactivating intestinal peptides glucagon like peptide-1 (GLP-1) and Gastric inhibitory polypeptide (GIP), which stimulates a decline in blood glucose levels. The aim of this study was to explore the inhibition activity of small molecule inhibitors to DPP-4 following a computational strategy based on docking studies and molecular dynamics simulations. The thorough docking protocol we applied allowed us to derive good correlation parameters between the predicted binding affinities (pKi) of the DPP-4 inhibitors and the experimental activity values (pIC50). Based on molecular docking receptor-ligand interactions, pharmacophore generation was carried out in order to identify the binding modes of structurally diverse compounds in the receptor active site. Consideration of the permanence and flexibility of DPP-4 inhibitor complexes by means of molecular dynamics (MD) simulation specified that the inhibitors maintained the binding mode observed in the docking study. The present study helps generate new information for further structural optimization and can influence the development of new DPP-4 inhibitors discoveries in the treatment of type-2 diabetes.

Disturbance of Arabidopsis thaliana microRNA-regulated pathways by Xcc bacterial effector proteins.

Plants are continuously subjected to infection by pathogens, including bacteria and viruses. Bacteria can inject a variety of effector proteins into the host to reprogram host defense mechanism. It is known that microRNAs participate in plant disease resistance to bacterial pathogens and previous studies have suggested that some bacterial effectors have evolved to disturb the host's microRNA-regulated pathways; and so enabling infection. In this study, the inter-species interaction between an Xanthomonas campestris pv campestris (Xcc) pathogen effector and Arabidopsis thaliana microRNA transcription promoter was investigated using three methods: (1) interolog, (2) alignment based on using transcription factor binding site profile matrix, and (3) the web-based binding site prediction tool, PATSER. Furthermore, we integrated another two data sets from our previous study into the present web-based system. These are (1) microRNA target genes and their downstream effects mediated by protein-protein interaction (PPI), and (2) the Xcc-Arabidopsis PPI information. This present work is probably the first comprehensive study of constructing pathways that comprises effector, microRNA, target genes and PPI for the study of pathogen-host interactions. It is expected that this study may help to elucidate the role of pathogen-host interplay in a plant's immune system. The database is freely accessible at: http://ppi.bioinfo.asia.edu.tw/EDMRP .

Comparison of risks factors for unplanned ICU transfer after ED admission in patients with infections and those without infections.

BACKGROUND: The objectives of this study were to compare the risk factors for unplanned intensive care unit (ICU) transfer after emergency department (ED) admission in patients with infections and those without infections and to explore the feasibility of using risk stratification tools for sepsis to derive a prediction system for such unplanned transfer. METHODS: The ICU transfer group included 313 patients, while the control group included 736 patients randomly selected from those who were not transferred to the ICU. Candidate variables were analyzed for association with unplanned ICU transfer in the 1049 study patients. RESULTS: Twenty-four variables were associated with unplanned ICU transfer. Sixteen (66.7%) of these variables displayed association in patients with infections and those without infections. These common risk factors included specific comorbidities, physiological responses, organ dysfunctions, and other serious symptoms and signs. Several common risk factors were statistically independent. CONCLUSIONS: The risk factors for unplanned ICU transfer in patients with infections were comparable to those in patients without infections. The risk factors for unplanned ICU transfer included variables from multiple dimensions that could be organized according to the PIRO (predisposition, insult/infection, physiological response, and organ dysfunction) model, providing the basis for the development of a predictive system.

Association of Prenatal Exposure to Antiseizure Medications With Creative and Executive Function at Age 4.5 Years.

BACKGROUND AND OBJECTIVES: Neurodevelopmental effects of fetal antiseizure medication (ASM) exposure on creativity and executive functions are poorly understood. We previously found fetal valproate exposure to adversely affect measures of creativity and executive functions. In this study, we examine fetal exposure of newer ASMs on these functions in children of women with epilepsy (WWE) compared with children of healthy women (HW). METHODS: The Maternal Outcomes and Neurodevelopmental Effects of Antiepileptic Drugs study is a multicenter NIH-funded prospective observational cohort study of WWE and HW enrolled in pregnancy and their offsprings. This report examines blindly assessed creativity and executive functions in 4.5-year-old children of WWE vs HW. In addition, exposure-dependent ASM effects during the third trimester were examined in children of WWE, using a ratio of maximum observed ASM concentrations and ratio of defined daily dose (ratio DDD). For polytherapy, ratios were summed across ASMs. Linear regression models adjusted for multiple potential confounding factors were conducted for all analyses. The primary outcome for 4.5-year-old children was the Torrance Test of Creative Thinking-Figural Creativity Index. Secondary outcomes included the Global Executive Composite Score from the Behavior Rating Inventory of Executive Function-Preschool Version and subscales and other indexes of both measures. RESULTS: The primary analysis included 251 children of WWE and 73 of HW. No differences in creativity or executive function were found between children of WWE vs HW. No ASM exposure-dependent effects were found for the creativity measures, but exposure-dependent effects for executive function were present for ratio ASM concentration and ratio DDD. DISCUSSION: Our findings at 4.5 years show no differences in creative thinking between children of WWE vs HW (-3.2 [-9.0 to 2.7], p = 0.286) or associations with fetal exposure to ASMs (-2.6 [-11.0 to 5.7], p = 0.530). Secondary analyses revealed fetal exposure-dependent effects for executive function in children of WWE (7.0 [2.9-11.2], p = 0.001), which are most marked for levetiracetam (12.9 [4.2-21.6], p = 0.004). Our findings suggest that even for relatively safe ASMs, dosing needs to be adjusted to concentrations that prevent seizures, but balance risks to the fetus that high concentrations may pose. TRIAL REGISTRATION INFORMATION: The study is registered at ClinicalTrials.gov as NCT01730170.

Dynamics of normalization underlying masking in human visual cortex.

Stimulus visibility can be reduced by other stimuli that overlap the same region of visual space, a process known as masking. Here we studied the neural mechanisms of masking in humans using source-imaged steady state visual evoked potentials and frequency-domain analysis over a wide range of relative stimulus strengths of test and mask stimuli. Test and mask stimuli were tagged with distinct temporal frequencies and we quantified spectral response components associated with the individual stimuli (self terms) and responses due to interaction between stimuli (intermodulation terms). In early visual cortex, masking alters the self terms in a manner consistent with a reduction of input contrast. We also identify a novel signature of masking: a robust intermodulation term that peaks when the test and mask stimuli have equal contrast and disappears when they are widely different. We fit all of our data simultaneously with family of a divisive gain control models that differed only in their dynamics. Models with either very short or very long temporal integration constants for the gain pool performed worse than a model with an integration time of ∼30 ms. Finally, the absolute magnitudes of the response were controlled by the ratio of the stimulus contrasts, not their absolute values. This contrast-contrast invariance suggests that many neurons in early visual cortex code relative rather than absolute contrast. Together, these results provide a more complete description of masking within the normalization framework of contrast gain control and suggest that contrast normalization accomplishes multiple functional goals.

Attenuation of low dose methylmercury and glutamate induced-cytotoxicity and tau phosphorylation by an N-methyl-D-aspartate antagonist in human neuroblastoma (SHSY5Y) cells.

Methylmercury (MeHg), a known neurotoxin, has been reported to alter glutamate homeostasis in the neuronal environment resulting in excitotoxicity. This study was conducted to investigate whether, and if so, under what conditions, that low dose MeHg would enhance the toxicity of glutamate and to what extent that blockade of NMDA receptors would alter MeHg and glutamate's toxicity in cultured neuroblastoma cells. Neuroblastoma cells (SH-SY5Y) were used in a cell culture model to study effects of MeHg, glutamate (glu), a calcium chelator (BAPTA-AM), and a noncompetitive NMDA antagonist, MK-801 on cell growth, cell survival, and phosphorylation of tau protein, as a measure of cellular events associated with tauopathies. Exposure of cells to a combination of MeHg (50 nM) and glutamate (1 mM) resulted in both a greater decrease in cell viability as well as a greater induction in tau phosphorylation, as compared to exposures with MeHg and glutamate alone. MK-801, an NMDA receptor antagonist, and the intracellular calcium chelator, BAPTA-AM, both significantly inhibited tau hyperphosphorylation and protected cells from the effects of combination exposures to glutamate and MeHg. These results may indicate that exposure to even nontoxic levels of MeHg may prime neuronal cells to be more susceptible to neuronal injury from excitotoxicants such as glutamate and thus may increase the likelihood of neurological disease states. In conclusion, low-dose MeHg-induced toxicity may be related to an increase in the cellular response to glutamate and that NMDA receptor antagonists may provide a potential treatment for MeHg-associated neurological diseases.

Validation of Gait Measurements on Short-Distance Walkways Using Azure Kinect DK in Patients Receiving Chronic Hemodialysis.

Muscle dysfunction, skeletal muscle fibrosis, and disability are associated with weakness in patients with end-stage renal disease. The main purpose of this study was to validate the effectiveness of a proposed system for gait monitoring on short-distance 1.5 m walkways in a dialysis center. Gaits with reduced speed and stride length, long sit-to-stand time (SST), two forward angles, and two unbalanced gait regions are defined in the proposed Kinect v3 gait measurement and analysis system (K3S) and have been considered clinical features in end-stage renal disease (ESRD) associated with poor dialysis outcomes. The stride and pace calibrations of the Kinect v3 system are based on the Zeno Walkway. Its single rating intraclass correlation (ICC) for the stride is 0.990, and its single rating ICC for the pace is 0.920. The SST calibration of Kinect v3 is based on a pressure insole; its single rating ICC for the SST is 0.871. A total of 75 patients on chronic dialysis underwent gait measurement and analysis during walking and weighing actions. After dialysis, patients demonstrated a smaller stride (p < 0.001) and longer SST (p < 0.001). The results demonstrate that patients' physical fitness was greatly reduced after dialysis. This study ensures patients' adequate physical gait strength to cope with the dialysis-associated physical exhaustion risk by tracing gait outliers. As decreased stride and pace are associated with an increased risk of falls, further studies are warranted to evaluate the clinical benefits of monitoring gait with the proposed reliable and valid system in order to reduce fall risk in hemodialysis patients.

The Epidemiological Analysis of COVID-19 Outbreaks in Nursing Homes during the Period of Omicron Variant Predominance.

BACKGROUND: The main purpose of this study was to evaluate the epidemic trend and risk factors associated with COVID-19 outbreaks in nursing homes during the period of Omicron variant predominance. METHODS: The study analyzed the risk factors associated with SARS-CoV-2 infection and death among the 327 residents and 129 healthcare workers (HCWs) in three hospital-affiliated nursing homes through a multivariate Cox regression model. RESULTS: The rates of receiving a COVID-19 booster dose were 70.3% for the residents and 93.0% for the healthcare workers (HCWs), respectively. A number of asymptomatic individuals, including 54 (16.5%) residents and 15 (11.6%) HCWs, were detected through mass screening surveillance tests. The COVID-19 infection rates during the outbreaks were 41.6% among residents and 48.1% among HCWs, respectively. The case fatality rate among residents was 10.3%. None of the HCWs were hospitalized or died. The multivariate Cox regression model showed that the risk of COVID-19 infection increased in males (HR 2.46; 95% CI 1.47-4.11; p = 0.001), Barthel index ≥ 61 (HR 1.93; 95% CI 1.18-3.17; p = 0.009), and dementia (HR 1.61; 95% CI 1.14-2.27; p = 0.007). The risk of COVID-19 death increased with pneumonia (HR 11.03; 95% CI 3.02-40.31; p < 0.001), hospitalization (HR 7.18; 95% CI 1.97-26.25; p = 0.003), and admission to an intensive care unit (HR 8.67; 95% CI 2.79-26.89; p < 0.001). CONCLUSIONS: This study highlighted the high infection rates with a substantial proportion of asymptomatic infections for both residents and HCWs, as well as a high case fatality rate for the residents among nursing homes during the Omicron epidemic period. We suggest implementing mass screening through regular surveillance testing as an effective strategy for early detection of COVID-19 and for preventing transmission during an epidemic period. Pneumonia is the primary risk associated with COVID-19 death. Early detection and prompt treatment of pneumonia for vulnerable residents in nursing homes are crucial to protect them from potential mortality.