Background
Telemedicine (TM) is the use of telecommunication systems to deliver health care at a distance. It has the potential to improve patient health outcomes, access to health care and reduce ...healthcare costs. As TM applications continue to evolve it is important to understand the impact TM might have on patients, healthcare professionals and the organisation of care.
Objectives
To assess the effectiveness, acceptability and costs of interactive TM as an alternative to, or in addition to, usual care (i.e. face‐to‐face care, or telephone consultation).
Search methods
We searched the Effective Practice and Organisation of Care (EPOC) Group's specialised register, CENTRAL, MEDLINE, EMBASE, five other databases and two trials registers to June 2013, together with reference checking, citation searching, handsearching and contact with study authors to identify additional studies.
Selection criteria
We considered randomised controlled trials of interactive TM that involved direct patient‐provider interaction and was delivered in addition to, or substituting for, usual care compared with usual care alone, to participants with any clinical condition. We excluded telephone only interventions and wholly automatic self‐management TM interventions.
Data collection and analysis
For each condition, we pooled outcome data that were sufficiently homogenous using fixed effect meta‐analysis. We reported risk ratios (RR) and 95% confidence intervals (CI) for dichotomous outcomes, and mean differences (MD) for continuous outcomes.
Main results
We included 93 eligible trials (N = 22,047 participants), which evaluated the effectiveness of interactive TM delivered in addition to (32% of studies), as an alternative to (57% of studies), or partly substituted for usual care (11%) as compared to usual care alone.
The included studies recruited patients with the following clinical conditions: cardiovascular disease (36), diabetes (21), respiratory conditions (9), mental health or substance abuse conditions (7), conditions requiring a specialist consultation (6), co morbidities (3), urogenital conditions (3), neurological injuries and conditions (2), gastrointestinal conditions (2), neonatal conditions requiring specialist care (2), solid organ transplantation (1), and cancer (1).
Telemedicine provided remote monitoring (55 studies), or real‐time video‐conferencing (38 studies), which was used either alone or in combination. The main TM function varied depending on clinical condition, but fell typically into one of the following six categories, with some overlap: i) monitoring of a chronic condition to detect early signs of deterioration and prompt treatment and advice, (41); ii) provision of treatment or rehabilitation (12), for example the delivery of cognitive behavioural therapy, or incontinence training; iii) education and advice for self‐management (23), for example nurses delivering education to patients with diabetes or providing support to parents of very low birth weight infants or to patients with home parenteral nutrition; iv) specialist consultations for diagnosis and treatment decisions (8), v) real‐time assessment of clinical status, for example post‐operative assessment after minor operation or follow‐up after solid organ transplantation (8) vi), screening, for angina (1).
The type of data transmitted by the patient, the frequency of data transfer, (e.g. telephone, e‐mail, SMS) and frequency of interactions between patient and healthcare provider varied across studies, as did the type of healthcare provider/s and healthcare system involved in delivering the intervention.
We found no difference between groups for all‐cause mortality for patients with heart failure (16 studies; N = 5239; RR:0.89, 95% CI 0.76 to 1.03, P = 0.12; I2 = 44%) (moderate to high certainty of evidence) at a median of six months follow‐up. Admissions to hospital (11 studies; N = 4529) ranged from a decrease of 64% to an increase of 60% at median eight months follow‐up (moderate certainty of evidence). We found some evidence of improved quality of life (five studies; N = 482; MD:‐4.39, 95% CI ‐7.94 to ‐0.83; P < 0.02; I2 = 0%) (moderate certainty of evidence) for those allocated to TM as compared with usual care at a median three months follow‐up. In studies recruiting participants with diabetes (16 studies; N = 2768) we found lower glycated haemoglobin (HbA1c %) levels in those allocated to TM than in controls (MD ‐0.31, 95% CI ‐0.37 to ‐0.24; P < 0.00001; I2= 42%, P = 0.04) (high certainty of evidence) at a median of nine months follow‐up. We found some evidence for a decrease in LDL (four studies, N = 1692; MD ‐12.45, 95% CI ‐14.23 to ‐10.68; P < 0.00001; I2 = 0%) (moderate certainty of evidence), and blood pressure (four studies, N = 1770: MD: SBP:‐4.33, 95% CI ‐5.30 to ‐3.35, P < 0.00001; I2 = 17%; DBP: ‐2.75 95% CI ‐3.28 to ‐2.22, P < 0.00001; I2 = 45% (moderate certainty evidence), in TM as compared with usual care.
Seven studies that recruited participants with different mental health and substance abuse problems, reported no differences in the effect of therapy delivered over video‐conferencing, as compared to face‐to‐face delivery. Findings from the other studies were inconsistent; there was some evidence that monitoring via TM improved blood pressure control in participants with hypertension, and a few studies reported improved symptom scores for those with a respiratory condition. Studies recruiting participants requiring mental health services and those requiring specialist consultation for a dermatological condition reported no differences between groups.
Authors' conclusions
The findings in our review indicate that the use of TM in the management of heart failure appears to lead to similar health outcomes as face‐to‐face or telephone delivery of care; there is evidence that TM can improve the control of blood glucose in those with diabetes. The cost to a health service, and acceptability by patients and healthcare professionals, is not clear due to limited data reported for these outcomes. The effectiveness of TM may depend on a number of different factors, including those related to the study population e.g. the severity of the condition and the disease trajectory of the participants, the function of the intervention e.g., if it is used for monitoring a chronic condition, or to provide access to diagnostic services, as well as the healthcare provider and healthcare system involved in delivering the intervention.
The genome of cowpea (Vigna unguiculata [L.] Walp.) Lonardi, Stefano; Muñoz‐Amatriaín, María; Liang, Qihua ...
The Plant journal : for cell and molecular biology,
June 2019, Letnik:
98, Številka:
5
Journal Article
Recenzirano
Odprti dostop
Summary
Cowpea (Vigna unguiculata L. Walp.) is a major crop for worldwide food and nutritional security, especially in sub‐Saharan Africa, that is resilient to hot and drought‐prone environments. An ...assembly of the single‐haplotype inbred genome of cowpea IT97K‐499‐35 was developed by exploiting the synergies between single‐molecule real‐time sequencing, optical and genetic mapping, and an assembly reconciliation algorithm. A total of 519 Mb is included in the assembled sequences. Nearly half of the assembled sequence is composed of repetitive elements, which are enriched within recombination‐poor pericentromeric regions. A comparative analysis of these elements suggests that genome size differences between Vigna species are mainly attributable to changes in the amount of Gypsy retrotransposons. Conversely, genes are more abundant in more distal, high‐recombination regions of the chromosomes; there appears to be more duplication of genes within the NBS‐LRR and the SAUR‐like auxin superfamilies compared with other warm‐season legumes that have been sequenced. A surprising outcome is the identification of an inversion of 4.2 Mb among landraces and cultivars, which includes a gene that has been associated in other plants with interactions with the parasitic weed Striga gesnerioides. The genome sequence facilitated the identification of a putative syntelog for multiple organ gigantism in legumes. A revised numbering system has been adopted for cowpea chromosomes based on synteny with common bean (Phaseolus vulgaris). An estimate of nuclear genome size of 640.6 Mbp based on cytometry is presented.
Significance Statement
State‐of‐the‐art technologies and assembly methods were used to generate a reference genome sequence of cowpea, a drought‐resilient crop on which millions of people in sub‐Saharan Africa depend as a source of protein. This sequence facilitated the identification of: repetitive elements and gene families expanded in cowpea compared with other closely related legumes; a large and apparently rare chromosomal inversion; and an interesting candidate gene that is associated with several domestication‐related traits.
Valvular heart disease (VHD) is expected to become more common as the population ages. However, current estimates of its natural history and prevalence are based on historical studies with potential ...sources of bias. We conducted a cross-sectional analysis of the clinical and epidemiological characteristics of VHD identified at recruitment of a large cohort of older people.
We enrolled 2500 individuals aged ≥65 years from a primary care population and screened for undiagnosed VHD using transthoracic echocardiography. Newly identified (predominantly mild) VHD was detected in 51% of participants. The most common abnormalities were aortic sclerosis (34%), mitral regurgitation (22%), and aortic regurgitation (15%). Aortic stenosis was present in 1.3%. The likelihood of undiagnosed VHD was two-fold higher in the two most deprived socioeconomic quintiles than in the most affluent quintile, and three-fold higher in individuals with atrial fibrillation. Clinically significant (moderate or severe) undiagnosed VHD was identified in 6.4%. In addition, 4.9% of the cohort had pre-existing VHD (a total prevalence of 11.3%). Projecting these findings using population data, we estimate that the prevalence of clinically significant VHD will double before 2050.
Previously undetected VHD affects 1 in 2 of the elderly population and is more common in lower socioeconomic classes. These unique data demonstrate the contemporary clinical and epidemiological characteristics of VHD in a large population-based cohort of older people and confirm the scale of the emerging epidemic of VHD, with widespread implications for clinicians and healthcare resources.
The Soybean Consensus Map 4.0 facilitated the anchoring of 95.6% of the soybean whole genome sequence developed by the Joint Genome Institute, Department of Energy, but its marker density was only ...sufficient to properly orient 66% of the sequence scaffolds. The discovery and genetic mapping of more single nucleotide polymorphism (SNP) markers were needed to anchor and orient the remaining genome sequence. To that end, next generation sequencing and high-throughput genotyping were combined to obtain a much higher resolution genetic map that could be used to anchor and orient most of the remaining sequence and to help validate the integrity of the existing scaffold builds.
A total of 7,108 to 25,047 predicted SNPs were discovered using a reduced representation library that was subsequently sequenced by the Illumina sequence-by-synthesis method on the clonal single molecule array platform. Using multiple SNP prediction methods, the validation rate of these SNPs ranged from 79% to 92.5%. A high resolution genetic map using 444 recombinant inbred lines was created with 1,790 SNP markers. Of the 1,790 mapped SNP markers, 1,240 markers had been selectively chosen to target existing unanchored or un-oriented sequence scaffolds, thereby increasing the amount of anchored sequence to 97%.
We have demonstrated how next generation sequencing was combined with high-throughput SNP detection assays to quickly discover large numbers of SNPs. Those SNPs were then used to create a high resolution genetic map that assisted in the assembly of scaffolds from the 8x whole genome shotgun sequences into pseudomolecules corresponding to chromosomes of the organism.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
A comprehensive transcriptome assembly of chickpea has been developed using 134.95 million Illumina single-end reads, 7.12 million single-end FLX/454 reads and 139,214 Sanger expressed sequence tags ...(ESTs) from >17 genotypes. This hybrid transcriptome assembly, referred to as C icer a rietinum T ranscriptome A ssembly version 2 (CaTA v2, available at http://data.comparative-legumes.org/transcriptomes/cicar/lista_cicar-201201), comprising 46,369 transcript assembly contigs (TACs) has an N50 length of 1,726 bp and a maximum contig size of 15,644 bp. Putative functions were determined for 32,869 (70.8%) of the TACs and gene ontology assignments were determined for 21,471 (46.3%). The new transcriptome assembly was compared with the previously available chickpea transcriptome assemblies as well as to the chickpea genome. Comparative analysis of CaTA v2 against transcriptomes of three legumes - Medicago , soybean and common bean, resulted in 27,771 TACs common to all three legumes indicating strong conservation of genes across legumes. CaTA v2 was also used for identification of simple sequence repeats (SSRs) and intron spanning regions (ISRs) for developing molecular markers. ISRs were identified by aligning TACs to the Medicago genome, and their putative mapping positions at chromosomal level were identified using transcript map of chickpea. Primer pairs were designed for 4,990 ISRs, each representing a single contig for which predicted positions are inferred and distributed across eight linkage groups. A subset of randomly selected ISRs representing all eight chickpea linkage groups were validated on five chickpea genotypes and showed 20% polymorphism with average polymorphic information content (PIC) of 0.27. In summary, the hybrid transcriptome assembly developed and novel markers identified can be used for a variety of applications such as gene discovery, marker-trait association, diversity analysis etc., to advance genetics research and breeding applications in chickpea and other related legumes.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Sexual dysfunction is a common complication for men with diabetes, yet little is known about the lived experiences of sexual difficulties within the context of diabetes, particularly in ...low-and-middle-income countries. This study explores how men with type 2 diabetes in three sub-Saharan African settings (Cape Town and Johannesburg, South Africa; Lilongwe, Malawi) perceive and experience sexual functioning and sexual well-being, and the biopsychosocial contexts in which these occur and are shaped.
We used a qualitative research design, including individual interviews (n = 15) and focus group discussions (n = 4). Forty-seven men were included in the study. We used an inductive thematic analysis approach to develop our findings. A biopsychosocial conceptual model on the relationship between chronic illness and sexuality informed the interpretation of findings.
Men across the study settings identified sexual difficulties as a central concern of living with diabetes. These difficulties went beyond biomedical issues of erectile dysfunction, comprising complex psychological and relational effects. Low self-esteem, related to a sense of loss of masculinity and reduced sexual and emotional intimacy in partner relationships were common experiences. Specific negative relational effects included suspicion of infidelity, mutual mistrust, general unhappiness, and fear of losing support from partners. These effects may impact on men's ability to cope with their diabetes. Further stressors were a lack of information about the reasons for their sexual difficulties, perceived lack of support from healthcare providers and an inability to communicate with partners about sexual difficulties.
More in-depth research is needed to better understand sexual functioning and well-being within the context of diabetes, and its potential impact on diabetes self-management. Holistic and patient-centered care should include raising awareness of sexual problems as a potential complication of diabetes amongst patients, their partners and care providers, and incorporating sexual well-being as part of routine clinical care.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Medicago truncatula is a model legume species that has been studied for decades to understand the symbiotic relationship between legumes and soil bacteria collectively named rhizobia. This symbiosis ...called nodulation is initiated in roots with the infection of root hair cells by the bacteria, as well as the initiation of nodule primordia from root cortical, endodermal, and pericycle cells, leading to the development of a new root organ, the nodule, where bacteria fix and assimilate the atmospheric dinitrogen for the benefit of the plant. Here, we report the isolation and use of the nuclei from mock and rhizobia-inoculated roots for the single nuclei RNA-seq (sNucRNA-seq) profiling to gain a deeper understanding of early responses to rhizobial infection in Medicago roots. A gene expression map of the Medicago root was generated, comprising 25 clusters, which were annotated as specific cell types using 119 Medicago marker genes and orthologs to Arabidopsis cell-type marker genes. A focus on root hair, cortex, endodermis, and pericycle cell types, showing the strongest differential regulation in response to a short-term (48 h) rhizobium inoculation, revealed not only known genes and functional pathways, validating the sNucRNA-seq approach, but also numerous novel genes and pathways, allowing a comprehensive analysis of early root symbiotic responses at a cell type-specific level.
Legume nodulation is the result of the symbiotic interaction between legume plants and soil bacteria collectively named rhizobia. In this study, the authors generated a single-cell resolution transcriptomic map of the Medicago root by using single-nucleus RNA-seq technolog. Based on this map, they further conducted a comprehensive transcriptomic analysis of the early root symbiotic responses at a cell-type-specific level.
Resistance and aerobic exercises are both recommended as effective treatments for people with type 2 diabetes. However, the optimum type of exercise for the disease remains to be determined to inform ...clinical decision-making and facilitate personalized exercise prescription.
Our objective was to investigate whether resistance exercise is comparable to aerobic exercise in terms of effectiveness and safety in people with type 2 diabetes.
PubMed, EMBASE, CENTRAL, CINAHL, and SPORTdiscus were systematically searched up to March 2013. The reference lists of eligible studies and relevant reviews were also checked.
We used the following criteria to select studies for inclusion in the review: (i) the study was a randomized controlled trial; (ii) the participants were people with type 2 diabetes aged 18 years or more; (iii) the trial compared resistance exercise with aerobic exercise for a duration of at least 8 weeks, with pre-determined frequency, intensity, and duration; and (iv) the trial provided relevant data on at least one of the following: glycaemic control, blood lipids, anthropometric measures, blood pressure, fitness, health status, and adverse events.
The assessment of study quality was based on the Cochrane Risk of Bias tool. For effectiveness measures, differences (resistance group minus aerobic group) in the changes from baseline with the two exercises were combined, using a random-effects model wherever possible. For adverse events, the relative risks (resistance group vs. aerobic group) were combined.
Twelve trials (n = 626) were included. Following the exercise interventions, there was a greater reduction of glycosylated hemoglobin with aerobic exercise than with resistance exercise (difference 0.18% (1.97 mmol/mol), 95% confidence interval (CI) 0.01, 0.36). This difference became non-significant with sensitivity analysis (p = 0.14). The differences in changes from baseline were also statistically significant for body mass index (difference 0.22, 95% CI 0.06, 0.39), peak oxygen consumption (difference -1.84 mL/kg/min, 95% CI -3.07, -0.62), and maximum heart rate (difference 3.44 beats per minute, 95% CI 2.49, 4.39). Relative risks for adverse events (all) and serious adverse events were 1.17 (95% CI 0.77, 1.79) and 0.89 (95% CI 0.18, 4.39), respectively.
Most included trials were short term (8 weeks to 6 months), and seven had important methodological limitations. Additionally, the meta-analyses for some of the secondary outcomes had a small number of participants or substantial statistical heterogeneity.
Although differences in some diabetic control and physical fitness measures between resistance exercise and aerobic exercise groups reached statistical significance, there is no evidence that they are of clinical importance. There is also no evidence that resistance exercise differs from aerobic exercise in impact on cardiovascular risk markers or safety. Using one or the other type of exercise for type 2 diabetes may be less important than doing some form of physical activity. Future long-term studies focusing on patient-relevant outcomes are warranted.
Abstract
Summary
The Genome Context Viewer is a visual data-mining tool that allows users to search across multiple providers of genome data for regions with similarly annotated content that may be ...aligned and visualized at the level of their shared functional elements. By handling ordered sequences of gene family memberships as a unit of search and comparison, the user interface enables quick and intuitive assessment of the degree of gene content divergence and the presence of various types of structural events within syntenic contexts. Insights into functionally significant differences seen at this level of abstraction can then serve to direct the user to more detailed explorations of the underlying data in other interconnected, provider-specific tools.
Availability and implementation
GCV is provided under the GNU General Public License version 3 (GPL-3.0). Source code is available at https://github.com/legumeinfo/lis_context_viewer.
Supplementary information
Supplementary data are available at Bioinformatics online.
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