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Motor activity fluctuations in healthy adults exhibit fractal patterns characterized by consistent temporal correlations across wide-ranging time scales. However, these patterns are disrupted by aging and psychiatric conditions. This study aims to investigate how fractal patterns vary across the sleep–wake cycle, differ based on individuals' recency of depression diagnosis, and change before and after a depressive episode.
Methods
Using actigraphy from two cohorts (n = 378), we examined fractal motor activity patterns both between individuals without depression and with varying recencies of depression and within individuals before and after depressive symptom recurrence. To evaluate fractal patterns, we quantified temporal correlations in motor activity fluctuations across different time scales using a scaling exponent, α. Linear mixed models were utilized to assess the influence of the sleep–wake cycle, (recency of) depression, and their interaction on α.
Results
Fractal activity patterns in all individuals varied across the sleep–wake cycle, showing stronger temporal correlations during wakefulness (larger α = 1.035 ± 0.003) and more random activity fluctuations during sleep (smaller α = 0.784 ± 0.004, p < 0.001). This sleep–wake difference was reduced in recently depressed individuals (1–6 months), leading to larger α during sleep (0.836 ± 0.017), compared to currently depressed (0.781 ± 0.018, p = 0.006), remitted (0.776 ± 0.014, p < 0.001), and never-depressed individuals (0.773 ± 0.016, p < 0.001). Moreover, remitted individuals who experienced depressive symptom recurrence during antidepressant tapering exhibited a larger α during sleep after the symptom onset as compared to before (after: α = 0.703 ± 0.022; before: α = 0.680 ± 0.022; p < 0.001).
Conclusions
These findings suggest a link between fractal motor activity patterns during sleep and depressive symptom recurrence in remitted individuals and those with recent depression.
Echinococcosis poses a significant threat to public health. The Chinese government has implemented prevention and control measures to mitigate the impact of the disease. By analyzing data from the Chinese Center for Disease Control and Prevention and the State Council of the People’s Republic of China, we found that implementation of these measures has reduced the infection rate by nearly 50% between 2004 to 2022 (from 0.3975 to 0.1944 per 100,000 person-years). Nonetheless, some regions still bear a significant disease burden, and lack of detailed information limites further evaluation of the effects on both alveolar and cystic echinococcosis. Our analysis supports the continuing implementation of these measures and suggests that enhanced wildlife management, case-based strategies, and surveillance systems will facilitate disease control.
The chemistry of Al transformation has been well documented, though little is known about the mechanisms of structural perturbation of Al precipitates by carbonates at a molecular level. The purpose of the present study was to investigate the structural perturbation of Al precipitates formed under the influence of carbonates. Initial carbonate/Al molar ratios (MRs) used were 0, 0.1, and 0.5 after aging for 32 days, then the samples were analyzed by X-ray absorption near edge structure spectroscopy (XANES), X-ray diffraction (XRD), Fourier-transform infrared absorption spectroscopy (FTIR), and chemical analysis. The XRD data were in accord with the FTIR results, which revealed that as the carbonate/Al MR was increased from 0 to 0.1, carbonate preferentially retarded the formation of gibbsite and had relatively little effect on the formation of bayerite. As the carbonate/Al MR was increased to 0.5, however, the crystallization of both gibbsite and bayerite was completely inhibited. The impact of carbonate on the nature of Al precipitates was also evident in the increase of adsorbed water and inorganic C contents with increasing carbonate/Al MR. The Al K- and L- edge XANES data provide the first evidence illustrating the change in the coordination number of Al from 6-fold to mixed 6- and 4-fold coordination in the structural network of short-range ordered (SRO) Al precipitates formed under the increasing perturbation of carbonate. The fluorescence yield spectra of the O K-edge show that the intensity of the peak at 534.5 eV assigned to σ* transitions of Al-O and O-H bonding decreased with increasing carbonate/Al MR. The XANES data, along with the evidence from XRD, FTIR, and chemical analysis showed clearly that carbonate caused the alteration of the coordination nature of the Al-O bonding through perturbation of the atomic bonding and structural configuration of Al hydroxides by complexation with Al in the SRO network of Al precipitates. The surface reactivity of an Al-O bond is related to its covalency and coordination geometry. The present findings were, therefore, of fundamental significance in understanding the low-temperature geochemistry of Al and its impacts on the transformation, transport, and fate of nutrients and pollutants in the ecosystem.
To analyse the natural course of infants with otitis media with effusion who failed universal newborn hearing screening and to explore the appropriate observation period.
Methods
This retrospective cohort analysis included infants with otitis media with effusion who failed universal newborn hearing screening every 3 months for 12 months.
Results
The average recovery time of the 155 infants was 7.08 ± 0.32 months after diagnosis. Multivariate Cox regression analysis confirmed that frequent reflux, maxillofacial deformities and initial hearing status were independent factors affecting recovery. Moreover, the cumulative recovery of most infants with mild hearing loss and infants with moderate hearing loss accompanied by frequent reflux was significantly higher at six months after diagnosis than at three months.
Conclusion
For most infants with mild hearing loss, as well as those with moderate hearing loss accompanied by frequent reflux, the observation period can be extended to six months after diagnosis.
We consider a two-dimensional (2-D) model of an autophoretic particle. Beyond a certain emission/absorption rate (characterized by a dimensionless Péclet number, $Pe$) the particle is known to undergo a bifurcation from a non-motile to a motile state, with different trajectories, going from a straight to a chaotic motion by increasing $Pe$. From the full model, we derive a reduced closed model which involves only two time-dependent complex amplitudes $C_1(t)$ and $C_2(t)$ corresponding to the first two Fourier modes of the solute concentration field. It consists of two coupled nonlinear ordinary differential equations for $C_1$ and $C_2$ and presents several advantages: (i) the straight and circular motions can be handled fully analytically; (ii) complex motions such as chaos can be analysed numerically very efficiently in comparison with the numerically expensive full model involving partial differential equations; (iii) the reduced model has a universal form dictated only by symmetries (meaning that the form of the equations does not depend on a given phoretic model); (iv) the model can be extended to higher Fourier modes. The derivation method is exemplified for a 2-D model, for simplicity, but can easily be extended to three dimensions, not only for the presently selected phoretic model, but also for any model in which chemical activity triggers locomotion. A typical example can be found, for example, in the field of cell motility involving acto-myosin kinetics. This strategy offers an interesting way to cope with swimmers on the basis of ordinary differential equations, allowing for analytical tractability and efficient numerical treatment.
Dietary patterns (DP) rich in plant foods are associated with improved health and reduced non-communicable disease risk. In October 2021, the Nutrition Society hosted a member-led conference, held online over 2 half days, exploring the latest research findings examining plant-rich DP and health. The aim of the present paper is to summarise the content of the conference and synopses of the individual speaker presentations are included. Topics included epidemiological analysis of plant-rich DP and health outcomes, the effects of dietary interventions which have increased fruit and vegetable (FV) intake on a range of health outcomes, how adherence to plant-rich DP is assessed, the use of biomarkers to assess FV intake and a consideration of how modifying behaviour towards increased FV intake could impact environmental outcomes, planetary health and food systems. In conclusion, although there are still considerable uncertainties which require further research, which were considered as part of the conference and are summarised in this review, adopting a plant-rich DP at a population level could have a considerable impact on diet and health outcomes, as well as planetary health.
The measurement and communication of the effect size of an independent variable on a dependent variable is critical to effective statistical analysis in the Social Sciences. We develop ideas about how to extend traditional methods of evaluating relationships in multivariate models to explain and illustrate the statistical power of a focal independent variable. Even with a growing acceptance of the need to report effect sizes, scholars in the management community have few well-established protocols or guidelines for reporting effect sizes. In this editorial essay, we: (1) review the necessity of reporting effect sizes; (2) discuss commonly used measures of effect size and accepted cut-offs for large, medium, and small effect sizes; (3) recommend standards for reporting effect sizes via verbal descriptions and graphical presentations; and (4) present best practice examples of reporting and discussing effect size. In summary, we provide guidance for authors on how to report and interpret effect sizes, advocating for rigor and completeness in statistical analysis.
The early identification and prediction of hand-foot-and-mouth disease (HFMD) play an important role in the disease prevention and control. However, suitable models are different in regions due to the differences in geography, social economy factors. We collected data associated with daily reported HFMD cases and weather factors of Zibo city in 2010~2019 and used the generalised additive model (GAM) to evaluate the effects of weather factors on HFMD cases. Then, GAM, support vectors regression (SVR) and random forest regression (RFR) models are used to compare predictive results. The annual average incidence was 129.72/100 000 from 2010 to 2019. Its distribution showed a unimodal trend, with incidence increasing from March, peaking from May to September. Our study revealed the nonlinear relationship between temperature, rainfall and relative humidity and HFMD cases and based on the predictive result, the performances of three models constructed ranked in descending order are: SVR > GAM> RFR, and SVR has the smallest prediction errors. These findings provide quantitative evidence for the prediction of HFMD for special high-risk regions and can help public health agencies implement prevention and control measures in advance.
ABSTRACT IMPACT: This is the first examination of risk factors for prolonged opioid use after an ICU stay and will inform efforts to strengthen prescribing guidelines and care transition models for patients after critical illness. OBJECTIVES/GOALS: The majority of patients in intensive care units (ICU) receive opioids during admission, and up to 25% receive a prescription at discharge. However, transitions of care and prolonged use after discharge remain unknown. We aim to characterize risk factors for prolonged opioid use after an ICU stay. METHODS/STUDY POPULATION: A retrospective study using insurance claims from Optum Clinformatics ®Data Mart was conducted for opioid-naive adult patients (18-64 years) with an ICU admission from 2010 to 2019. The primary outcome was new persistent opioid use, defined as a continued prescription fill 91-180 days after discharge, in addition to a fill in the first 90 days. The primary exposure was an opioid fill at discharge. The ICU admission was characterized using the Clinical Classification System from the Agency of Healthcare Research and Quality, based on patients’primary diagnosis code. Diagnoses were combined into 11 groups highlighting the affected organ system/mechanism of injury. Logistic regression evaluated the associations of patient demographic and clinical characteristics with the probability of persistent opioid use. RESULTS/ANTICIPATED RESULTS: In this cohort of 90,721 patients discharged from the ICU, 3.3% continued to fill opioids at 6 months. An opioid prescription fill (OR 3.1; 95% CI 28 - 3.3) and benzodiazepine prescription fill (OR 1.6; 95% CI 1.4 - 1.8) within 3 days of ICU discharge were each significantly associated with the development of new persistent opioid use. Patient diagnosis groups of Musculoskeletal/Trauma (OR 2.3; 95% CI 2.0 - 2.6), Neoplasms (OR 1.6; 95% CI 1.5 - 1.9), and GI/Hepatobiliary (OR 1.5; 95% CI 1.3 - 1.8) were significantly more likely to develop new persistent use when compared to the Cardiovascular diagnosis group. DISCUSSION/SIGNIFICANCE OF FINDINGS: Opioid prescriptions at discharge after an ICU stay increase the odds of prolonged opioid use. These results will inform efforts to strengthen prescribing guidelines and care models after a critical illness. Further work will characterize the trajectory of prescribing and patient exposure to high-risk prescribing after ICU discharge.
Before coronavirus disease 2019 (COVID-19), few hospitals had fully tested emergency surge plans. Uncertainty in the timing and degree of surge complicates planning efforts, putting hospitals at risk of being overwhelmed. Many lack access to hospital-specific, data-driven projections of future patient demand to guide operational planning. Our hospital experienced one of the largest surges in New England. We developed statistical models to project hospitalizations during the first wave of the pandemic. We describe how we used these models to meet key planning objectives. To build the models successfully, we emphasize the criticality of having a team that combines data scientists with frontline operational and clinical leadership. While modeling was a cornerstone of our response, models currently available to most hospitals are built outside of their institution and are difficult to translate to their environment for operational planning. Creating data-driven, hospital-specific, and operationally relevant surge targets and activation triggers should be a major objective of all health systems.
Klebsiella pneumoniae is a common pathogen associated with nosocomial infections and is characterised serologically by capsular polysaccharide (K) and lipopolysaccharide O antigens. We surveyed a total of 348 non-duplicate K. pneumoniae clinical isolates collected over a 1-year period in a tertiary care hospital, and determined their O and K serotypes by sequencing of the wbb Y and wzi gene loci, respectively. Isolates were also screened for antimicrobial resistance and hypervirulent phenotypes; 94 (27.0%) were identified as carbapenem-resistant (CRKP) and 110 (31.6%) as hypervirulent (hvKP). isolates fell into 58 K, and six O types, with 92.0% and 94.2% typeability, respectively. The predominant K types were K14K64 (16.38%), K1 (14.66%), K2 (8.05%) and K57 (5.46%), while O1 (46%), O2a (27.9%) and O3 (11.8%) were the most common. CRKP and hvKP strains had different serotype distributions with O2a:K14K64 (41.0%) being the most frequent among CRKP, and O1:K1 (26.4%) and O1:K2 (17.3%) among hvKP strains. Serotyping by gene sequencing proved to be a useful tool to inform the clinical epidemiology of K. pneumoniae infections and provides valuable data relevant to vaccine design.
Epidemiological studies indicate that individuals with one type of mental disorder have an increased risk of subsequently developing other types of mental disorders. This study aimed to undertake a comprehensive analysis of pair-wise lifetime comorbidity across a range of common mental disorders based on a diverse range of population-based surveys.
Methods
The WHO World Mental Health (WMH) surveys assessed 145 990 adult respondents from 27 countries. Based on retrospectively-reported age-of-onset for 24 DSM-IV mental disorders, associations were examined between all 548 logically possible temporally-ordered disorder pairs. Overall and time-dependent hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated using Cox proportional hazards models. Absolute risks were estimated using the product-limit method. Estimates were generated separately for men and women.
Results
Each prior lifetime mental disorder was associated with an increased risk of subsequent first onset of each other disorder. The median HR was 12.1 (mean = 14.4; range 5.2–110.8, interquartile range = 6.0–19.4). The HRs were most prominent between closely-related mental disorder types and in the first 1–2 years after the onset of the prior disorder. Although HRs declined with time since prior disorder, significantly elevated risk of subsequent comorbidity persisted for at least 15 years. Appreciable absolute risks of secondary disorders were found over time for many pairs.
Conclusions
Survey data from a range of sites confirms that comorbidity between mental disorders is common. Understanding the risks of temporally secondary disorders may help design practical programs for primary prevention of secondary disorders.
We describe system verification tests and early science results from the pulsar processor (PTUSE) developed for the newly commissioned 64-dish SARAO MeerKAT radio telescope in South Africa. MeerKAT is a high-gain (
${\sim}2.8\,\mbox{K Jy}^{-1}$
) low-system temperature (
${\sim}18\,\mbox{K at }20\,\mbox{cm}$
) radio array that currently operates at 580–1 670 MHz and can produce tied-array beams suitable for pulsar observations. This paper presents results from the MeerTime Large Survey Project and commissioning tests with PTUSE. Highlights include observations of the double pulsar
$\mbox{J}0737{-}3039\mbox{A}$
, pulse profiles from 34 millisecond pulsars (MSPs) from a single 2.5-h observation of the Globular cluster Terzan 5, the rotation measure of Ter5O, a 420-sigma giant pulse from the Large Magellanic Cloud pulsar PSR
$\mbox{J}0540{-}6919$
, and nulling identified in the slow pulsar PSR J0633–2015. One of the key design specifications for MeerKAT was absolute timing errors of less than 5 ns using their novel precise time system. Our timing of two bright MSPs confirm that MeerKAT delivers exceptional timing. PSR
$\mbox{J}2241{-}5236$
exhibits a jitter limit of
$<4\,\mbox{ns h}^{-1}$
whilst timing of PSR
$\mbox{J}1909{-}3744$
over almost 11 months yields an rms residual of 66 ns with only 4 min integrations. Our results confirm that the MeerKAT is an exceptional pulsar telescope. The array can be split into four separate sub-arrays to time over 1 000 pulsars per day and the future deployment of S-band (1 750–3 500 MHz) receivers will further enhance its capabilities.
Metabolic abnormality is common among schizophrenia patients. Some metabolic traits were found associated with subgroups of schizophrenia patients.
Objectives:
We examined a possible relationship between metabolic abnormality and psychosis profile in schizophrenia patients.
Method:
Three hundred and seventy-two chronic schizophrenia patients treated with antipsychotics for more than 2 years were assessed with the Positive and Negative Syndrome Scale. A set of metabolic traits was measured at scheduled checkpoints between October 2004 and September 2006.
Results:
Multiple regressions adjusted for sex showed negative correlations between body mass index (BMI) and total score and all subscales; triglycerides (TG) was negatively correlated with total score and negative syndrome, while HDLC was positively correlated with negative syndrome. When sex interaction was concerned, total score was negatively correlated with BMI but not with others; negative syndrome was negatively correlated with BMI and positively with HDLC. No metabolic traits were correlated with positive syndrome or general psychopathology.
Conclusions:
Loss of body weight is a serious health problem in schizophrenia patients with severe psychosis syndrome, especially the negative syndrome. Schizophrenia patients with severe negative syndrome may have a distinct lipid pathophysiology in comparison with those who were less severe in the domain.
Many MRI studies have cited major depression, with or without anti-depressive treatment, associated with structural plasticity changing in several brain regions. Few of these studies researched the effect of the anti-depressive treatment, electroconvulsive therapy (ECT), on depression.
Objective
To assess the influence of ECT on the brain structure change during the treatment process by utilizing the voxel-based morphometry (VBM) analysis.
Aims
To determine whether ECT alter brain structure.
Methods
We performed HAMD ratings and MRI scans on 12 depressive patients during ECT, analyzing the data by VBM with SPM8 software's family-wise error correction (FWE).
Results
The researchers found volumes changes in white matter in 37 regions between pre-ECT and post-ECT1, but only one region changing between pre-ECT and post-ECT8. Seven regions changing in grey matter between pre-ECT and post-ECT 1⌧but none regions changing between pre-ECT and post-ECT8.
Conclusions
The density changes in several brain regions after a single ECT stimuli, but return to the original level after completing the eighth ECT. Our finding supports that ECT may play a temporary role in treating major depression but do not permanently alter the structures of brain.
The output of many healthy physiological systems displays fractal fluctuations with self-similar temporal structures. Altered fractal patterns are associated with pathological conditions. There is evidence that patients with bipolar disorder have altered daily behaviors.
Methods
To test whether fractal patterns in motor activity are altered in patients with bipolar disorder, we analyzed 2-week actigraphy data collected from 106 patients with bipolar disorder type I in a euthymic state, 73 unaffected siblings of patients, and 76 controls. To examine the link between fractal patterns and symptoms, we analyzed 180-day actigraphy and mood symptom data that were simultaneously collected from 14 patients.
Results
Compared to controls, patients showed excessive regularity in motor activity fluctuations at small time scales (<1.5 h) as quantified by a larger scaling exponent (α1 > 1), indicating a more rigid motor control system. α1 values of siblings were between those of patients and controls. Further examinations revealed that the group differences in α1 were only significant in females. Sex also affected the group differences in fractal patterns at larger time scales (>2 h) as quantified by scaling exponent α2. Specifically, female patients and siblings had a smaller α2 compared to female controls, indicating more random activity fluctuations; while male patients had a larger α2 compared to male controls. Interestingly, a higher weekly depression score was associated with a lower α1 in the subsequent week.
Conclusions
Our results show sex- and scale-dependent alterations in fractal activity regulation in patients with bipolar disorder. The mechanisms underlying the alterations are yet to be determined.
A systematic review and network meta-analysis were conducted to assess the relative efficacy of internal or external teat sealants given at dry-off in dairy cattle. Controlled trials were eligible if they assessed the use of internal or external teat sealants, with or without concurrent antimicrobial therapy, compared to no treatment or an alternative treatment, and measured one or more of the following outcomes: incidence of intramammary infection (IMI) at calving, IMI during the first 30 days in milk (DIM), or clinical mastitis during the first 30 DIM. Risk of bias was based on the Cochrane Risk of Bias 2.0 tool with modified signaling questions. From 2280 initially identified records, 32 trials had data extracted for one or more outcomes. Network meta-analysis was conducted for IMI at calving. Use of an internal teat sealant (bismuth subnitrate) significantly reduced the risk of new IMI at calving compared to non-treated controls (RR = 0.36, 95% CI 0.25–0.72). For comparisons between antimicrobial and teat sealant groups, concerns regarding precision were seen. Synthesis of the primary research identified important challenges related to the comparability of outcomes, replication and connection of interventions, and quality of reporting of study conduct.
A systematic review and network meta-analysis were conducted to assess the relative efficacy of antimicrobial therapy given to dairy cows at dry-off. Eligible studies were controlled trials assessing the use of antimicrobials compared to no treatment or an alternative treatment, and assessed one or more of the following outcomes: incidence of intramammary infection (IMI) at calving, incidence of IMI during the first 30 days in milk (DIM), or incidence of clinical mastitis during the first 30 DIM. Databases and conference proceedings were searched for relevant articles. The potential for bias was assessed using the Cochrane Risk of Bias 2.0 algorithm. From 3480 initially identified records, 45 trials had data extracted for one or more outcomes. Network meta-analysis was conducted for IMI at calving. The use of cephalosporins, cloxacillin, or penicillin with aminoglycoside significantly reduced the risk of new IMI at calving compared to non-treated controls (cephalosporins, RR = 0.37, 95% CI 0.23–0.65; cloxacillin, RR = 0.55, 95% CI 0.38–0.79; penicillin with aminoglycoside, RR = 0.42, 95% CI 0.26–0.72). Synthesis revealed challenges with a comparability of outcomes, replication of interventions, definitions of outcomes, and quality of reporting. The use of reporting guidelines, replication among interventions, and standardization of outcome definitions would increase the utility of primary research in this area.
A systematic review and network meta-analysis were conducted to assess the relative efficacy of antimicrobial therapy for clinical mastitis in lactating dairy cattle. Controlled trials in lactating dairy cattle with natural disease exposure were eligible if they compared an antimicrobial treatment to a non-treated control, placebo, or a different antimicrobial, for the treatment of clinical mastitis, and assessed clinical or bacteriologic cure. Potential for bias was assessed using a modified Cochrane Risk of Bias 2.0 tool. From 14775 initially identified records, 54 trials were assessed as eligible. Networks were established for bacteriologic cure by bacterial species group, and clinical cure. Disparate networks among bacteriologic cures precluded meta-analysis. Network meta-analysis was conducted for trials assessing clinical cure, but lack of precision of point estimates resulted in wide credibility intervals for all treatments, with no definitive conclusions regarding relative efficacy. Consideration of network geometry can inform future research to increase the utility of current and previous work. Replication of intervention arms and consideration of connection to existing networks would improve the future ability to determine relative efficacy. Challenges in the evaluation of bias in primary research stemmed from a lack of reporting. Consideration of reporting guidelines would also improve the utility of future research.