No abstract available.
Electrodes*

Background/Aims: High-resolution extracellular mapping has improved our understanding of bioelectric slow-wave and spike-burst activity in the small intestine. The spatiotemporal correlation of electrophysiology and motility patterns is of critical interest to intestinal function but remains incompletely defined. Methods: Intestinal jejunum segments from in vivo pigs and rabbits were exteriorized, and simultaneous high-resolution extracellular recordings and video recordings were performed. Contractions were quantified with strain fields, and the frequencies and velocities of motility patterns were calculated. The amplitudes, frequencies, and velocities of slow-wave propagation patterns and spike-bursts were quantified and visualized. In addition, the duration, size and energy of spike-burst patches were quantified. Results: Slow-wave associated spike-bursts activated periodically at 10.8 ± 4.0 cycles per minute (cpm) in pigs and 10.2 ± 3.2 cpm in rabbits, while independent spike-bursts activated at a frequency of 3.2 ± 1.8 cpm. Independent spike-bursts had higher amplitude and longer duration than slow-wave associated spike-bursts (1.4 ± 0.8 mV vs 0.1 ± 0.1 mV, P < 0.001; 1.8 ± 1.4 seconds vs 0.8 ± 0.3 seconds, P < 0.001 in pigs). Spike-bursts that activated as longitudinal or circumferential patches were associated with contractions in the respective directions. Spontaneous peristaltic contractions were elicited by independent spike-bursts and travelled slower than slow-wave velocity (3.7 ± 0.5 mm/sec vs 10.1 ± 4.7 mm/sec, P = 0.007). Cyclic peristaltic contractions were driven by slow-wave associated spike-bursts and were coupled to slow-wave velocity and frequency in rabbit (14.2 ± 2.3 mm/sec vs 11.5 ± 4.6 mm/sec,P = 0.162; 11.0 ± 0.6 cpm vs 10.8 ± 0.6 cpm, P= 0.970). Conclusions Motility patterns were dictated by patterns of spike-burst patches. When spike-bursts were coupled to slow-waves, periodic motility patterns were observed, while when spike-bursts were not coupled to slow-waves, spontaneous aperiodic motility patterns were captured.

INTRODUCTIONThe incidence of newly diagnosed older patients diagnosed with human immunodeficiency virus (HIV) has increased worldwide in recent years. In this study, we compared the demographics and clinical presentation of younger and older patients in our HIV sentinel cohort.

MATERIALS AND METHODSAmong all HIV patients presenting to the Communicable Disease Centre (CDC), Singapore from 2006 to 2011, 793 were randomly included in our cohort, representing about 50% of the patients seen during that period. We collected demographic, clinical, laboratory, and outcome data from patient records to compare younger (<50 years old) and older (≥50 years old) HIV patients.

RESULTSOlder patients comprised 27.1% of our HIV cohort and presented with lower median CD4 T cell counts (65 cells/mm³, interquartile range [IQR]: 27 to 214 cells/mm³) compared to younger patients (250 cells/mm³, IQR: 74 to 400 cells/mm³; P <0.001). The median time from HIV diagnosis to initiation of antiretroviral therapy (ART) differed significantly for both age groups as well (49 days for patients <50 years old, IQR: 18 to 294 days; versus 35 days for patients ≥50 years old, IQR: 14 to 102 days; P = 0.008). More of our younger patients were single (72.2%) or homosexual (44.1%), in contrast to older patients, of whom 48.8% were married and 84.7% were heterosexual.

CONCLUSIONUpon comparison of our younger and older patients, we identified distinct differences in risk transmission and clinical presentation. Increased awareness of older patients at risk of HIV may improve time to diagnosis among this age group.

Age Factors ; Anti-Retroviral Agents ; therapeutic use ; CD4 Lymphocyte Count ; statistics & numerical data ; Female ; HIV Seropositivity ; drug therapy ; epidemiology ; physiopathology ; Humans ; Male ; Medical Audit ; Middle Aged ; Retrospective Studies ; Singapore ; epidemiology

BACKGROUND/AIMS: It is now recognised that gastric dysrhythmias are best characterised by their spatial propagation pattern. Hyperglycemia is an important cause of gastric slow wave dysrhythmia, however, the spatiotemporal patterns of dysrhythmias in this context have not been investigated. This study aims to investigate the relationship between hyperglycemia and the patterns of dysrhythmias by employing high-resolution (multi-electrode) mapping simultaneously at the anterior and posterior gastric serosa. METHODS: High-resolution mapping (8 × 16 electrodes per serosal) was performed in 4 anesthetized hounds. Baseline recordings (21 ± 8 minutes) were followed by intravenous injection of glucagon (0.5 mg per dose) and further recordings (59 ± 15 minutes). Blood glucose levels were monitored manually using a glucose sensing kit at regular 5-minute intervals. Slow wave activation maps, amplitudes, velocity, anisotropic ratio, and frequency were calculated. Differences were compared between baseline and post glucagon injection. RESULTS: Baseline slow waves propagated symmetrically and antegrade. The blood glucose levels were increased by an average of 112% compared to the baseline by the end of the recordings. All subjects demonstrated elevated incidence of slow wave dysrhythmias following injection compared to the baseline (48 ± 23% vs 6 ± 4%, P < 0.05). Dysrhythmias arose simultaneously or independently on anterior and posterior serosa. Spatial dysrhythmias occurred before and persisted after the onset and disappearance of temporal dysrhythmias. CONCLUSIONS: Infusion of glucagon induced gastric slow wave dysrhythmias, which occurred across a heterogeneous range of patterns and frequencies. The spatial dysrhythmias of gastric slow waves were shown to be more prevalent and persisted over a longer period of time compared to the temporal dysrhythmias.
Blood Glucose ; Electrodes ; Electrophysiology ; Gastrointestinal Tract ; Glucagon ; Glucose ; Hyperglycemia ; Incidence ; Injections, Intravenous ; Interstitial Cells of Cajal ; Myoelectric Complex, Migrating ; Serous Membrane

BACKGROUND/AIMS: Small intestine motility is governed by an electrical slow wave activity, and abnormal slow wave events have been associated with intestinal dysmotility. High-resolution (HR) techniques are necessary to analyze slow wave propagation, but progress has been limited by few available electrode options and laborious manual analysis. This study presents novel methods for in vivo HR mapping of small intestine slow wave activity. METHODS: Recordings were obtained from along the porcine small intestine using flexible printed circuit board arrays (256 electrodes; 4 mm spacing). Filtering options were compared, and analysis was automated through adaptations of the falling-edge variable-threshold (FEVT) algorithm and graphical visualization tools. RESULTS: A Savitzky-Golay filter was chosen with polynomial-order 9 and window size 1.7 seconds, which maintained 94% of slow wave amplitude, 57% of gradient and achieved a noise correction ratio of 0.083. Optimized FEVT parameters achieved 87% sensitivity and 90% positive-predictive value. Automated activation mapping and animation successfully revealed slow wave propagation patterns, and frequency, velocity, and amplitude were calculated and compared at 5 locations along the intestine (16.4 +/- 0.3 cpm, 13.4 +/- 1.7 mm/sec, and 43 +/- 6 microV, respectively, in the proximal jejunum). CONCLUSIONS: The methods developed and validated here will greatly assist small intestine HR mapping, and will enable experimental and translational work to evaluate small intestine motility in health and disease.
Electrodes ; Electrophysiology ; Forced Expiratory Volume ; Gastrointestinal Motility ; Interstitial Cells of Cajal ; Intestine, Small ; Intestines ; Noise

Purpose: Patients with cancer are particularly vulnerable to coronavirus disease (COVID). Transportation barriers made travel to obtain medical care more difficult during the pandemic. Whether these factors led to changes in the distance traveled for radiotherapy and the coordinated location of radiation treatment is unknown. Materials and Methods: We analyzed patients across 60 cancer sites in the National Cancer Database from 2018 to 2020. Demographic and clinical variables were analyzed for changes in distance traveled for radiotherapy. We designated the facilities in the 99th percentile or above in terms of the proportion of patients who traveled more than 200 miles as “destination facilities.” We defined “coordinated care” as undergoing radiotherapy at the same facility where the cancer was diagnosed. Results: We evaluated 1,151,954 patients. There was a greater than 1% decrease in the proportion of patients treated in the Mid-Atlantic States. Mean distance traveled from place of residence to radiation treatment decreased from 28.6 to 25.9 miles, and the proportion traveling greater than 50 miles decreased from 7.7% to 7.1%. At “destination facilities,” the proportion traveling more than 200 miles decreased from 29.3% in 2018 to 24% in 2020. In comparison, at the other hospitals, the proportion traveling more than 200 miles decreased from 1.07% to 0.97%. In 2020, residing in a rural area resulted in a lower odds of having coordinated care (multivariable odds ratio = 0.89; 95% confidence interval, 0.83–0.95). Conclusion The first year of the COVID pandemic measurably impacted the location of U.S. radiation therapy treatment.

The complete picture regarding transmission modes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is unknown. This review summarises the available evidence on its transmission modes, our preliminary research findings and implications for infection control policy, and outlines future research directions. Environmental contamination has been reported in hospital settings occupied by infected patients, and is higher in the first week of illness. Transmission via environmental surfaces or fomites is likely, but decontamination protocols are effective in minimising this risk. The extent of airborne transmission is also unclear. While several studies have detected SARS-CoV-2 ribonucleic acid in air samples, none has isolated viable virus in culture. Transmission likely lies on a spectrum between droplet and airborne transmission, depending on the patient, disease and environmental factors. Singapore's current personal protective equipment and isolation protocols are sufficient to manage this risk.
COVID-19 ; Hospitals ; Humans ; Infection Control/methods* ; Personal Protective Equipment ; SARS-CoV-2