Neutrophils in cancer: neutral no more

Neutrophils are indispensable antagonists of microbial infection and facilitators of wound healing. In the cancer setting, a newfound appreciation for neutrophils has come into view. The traditionally held belief that neutrophils are inert bystanders is being challenged by the recent literature. Emerging evidence indicates that tumours manipulate neutrophils, sometimes early in their differentiation process, to create diverse phenotypic and functional polarization states able to alter tumour behaviour. In this Review, we discuss the involvement of neutrophils in cancer initiation and progression, and their potential as clinical biomarkers and therapeutic targets

Discerning Tumor Status from Unstructured MRI Reports—Completeness of Information in Existing Reports and Utility of Automated Natural Language Processing

Information in electronic medical records is often in an unstructured free-text format. This format presents challenges for expedient data retrieval and may fail to convey important findings. Natural language processing (NLP) is an emerging technique for rapid and efficient clinical data retrieval. While proven in disease detection, the utility of NLP in discerning disease progression from free-text reports is untested. We aimed to (1) assess whether unstructured radiology reports contained sufficient information for tumor status classification; (2) develop an NLP-based data extraction tool to determine tumor status from unstructured reports; and (3) compare NLP and human tumor status classification outcomes. Consecutive follow-up brain tumor magnetic resonance imaging reports (2000–­2007) from a tertiary center were manually annotated using consensus guidelines on tumor status. Reports were randomized to NLP training (70%) or testing (30%) groups. The NLP tool utilized a support vector machines model with statistical and rule-based outcomes. Most reports had sufficient information for tumor status classification, although 0.8% did not describe status despite reference to prior examinations. Tumor size was unreported in 68.7% of documents, while 50.3% lacked data on change magnitude when there was detectable progression or regression. Using retrospective human classification as the gold standard, NLP achieved 80.6% sensitivity and 91.6% specificity for tumor status determination (mean positive predictive value, 82.4%; negative predictive value, 92.0%). In conclusion, most reports contained sufficient information for tumor status determination, though variable features were used to describe status. NLP demonstrated good accuracy for tumor status classification and may have novel application for automated disease status classification from electronic databases

The association between baseline persistent pain and weight change in patients attending a specialist weight management service

To quantify the influence of baseline pain levels on weight change at one-year follow-up in patients attending a National Health Service specialist weight management programme.We compared one-year follow-up weight (body mass) change between patient sub-groups of none-to-mild, moderate, and severe pain at baseline. A mean sub-group difference in weight change of ≥5kg was considered clinically relevant.Of the 141 complete cases, n = 43 (30.5%) reported none-to-mild pain, n = 44 (31.2%) reported moderate pain, and n = 54 (38.3%) reported severe pain. Covariate-adjusted mean weight loss (95%CI) was similar for those with none-to-mild (8.1kg (4.2 to 12.0kg)) and moderate pain (8.3kg (4.9 to 11.7kg). The mean weight loss of 3.0kg (-0.4 to 6.4kg) for the severe pain group was 5.1kg (-0.6 to 10.7, p = 0.08) lower than the none-to-mild pain group and 5.3kg (0.4 to 10.2kg, p = 0.03) lower than the moderate pain group.Patients with severe pain upon entry to a specialist weight management service in England achieve a smaller mean weight loss at one-year follow-up than those with none-to-moderate pain. The magnitude of the difference in mean weight loss was clinically relevant, highlighting the importance of addressing severe persistent pain in obese patients undertaking weight management programmes

Early to late sparing of radiation damage to the parotid gland by adrenergic and muscarinic receptor agonists

Damage to salivary glands after radiotherapeutic treatment of head and neck tumours can severely impair the quality of life of the patients. In the current study we have investigated the early-to-late pathogenesis of the parotid gland after radiation. Also the ability to ameliorate the damage using pretreatment with adrenergic or muscarinic receptor agonists is studied. Rats were locally irradiated with or without i.p. pretreatment with phenylephrine (α-adrenoceptor agonist, 5 mg kg−1), isoproterenol (β-adrenoceptor agonist, 5 mg kg−1), pilocarpine (4 mg kg−1), methacholine (3.75 mg kg−1) (muscarinic receptor agonists) or methacholine plus phenylephrine. Parotid salivary flow rate, amylase secretion, the number of cells and gland histology were monitored sequentially up to 240 days postirradiation. The effects were described in 4 distinct phases. The first phase (0–10 days) was characterised by a rapid decline in flow rate without changes in amylase secretion or acinar cell number. The second phase (10–60 days) consists of a decrease in amylase secretion and is paralleled by acinar cell loss. Flow rate, amylase secretion and acinar cell numbers do not change in the third phase (60–120 days). The fourth phase (120–240 days) is determined by a further deterioration of gland function but an increase in acinar cell number, albeit with poor tissue morphology. All drug pretreatments used could reduce radiation effects in phase I and II. The protective effects were lost during phase IV, with the exception of methacholine plus phenylephrine pretreatment. The latter combination of drugs ameliorated radiation-damage throughout the entire follow-up time. The data show that combined pre-irradiation stimulation of muscarinic acetylcholine receptors with methacholine plus α-adrenoceptors with phenylephrine can reduce both early and late damage, possibly involving the PLC/PIP2 second messenger pathways. This opens perspectives for the development of clinical applicable methods for long-term sparing of parotid glands subjected to radiotherapy of head and neck cancer patients. © 2001 Cancer Research Campaignhttp://www.bjcancer.co

Respiratory viruses in children hospitalized for acute lower respiratory tract infection in Ghana

<p>Abstract</p> <p>Background</p> <p>Acute respiratory tract infections are one of the major causes of morbidity and mortality among young children in developing countries. Information on the viral aetiology of acute respiratory infections in developing countries is very limited. The study was done to identify viruses associated with acute lower respiratory tract infection among children less than 5 years.</p> <p>Method</p> <p>Nasopharyngeal samples and blood cultures were collected from children less than 5 years who have been hospitalized for acute lower respiratory tract infection. Viruses and bacteria were identified using Reverse Transcriptase Real-Time Polymerase Chain Reaction and conventional biochemical techniques.</p> <p>Results</p> <p>Out of 128 patients recruited, 33(25.88%%, 95%CI: 18.5% to 34.2%) were positive for one or more viruses. Respiratory Syncytial Virus (RSV) was detected in 18(14.1%, 95%CI: 8.5% to 21.3%) patients followed by Adenoviruses (AdV) in 13(10.2%, 95%CI: 5.5% to 16.7%), Parainfluenza (PIV type: 1, 2, 3) in 4(3.1%, 95%CI: 0.9% to 7.8%) and influenza B viruses in 1(0.8%, 95%CI: 0.0 to 4.3). Concomitant viral and bacterial co-infection occurred in two patients. There were no detectable significant differences in the clinical signs, symptoms and severity for the various pathogens isolated. A total of 61.1% (22/36) of positive viruses were detected during the rainy season and Respiratory Syncytial Virus was the most predominant.</p> <p>Conclusion</p> <p>The study has demonstrated an important burden of respiratory viruses as major causes of childhood acute respiratory infection in a tertiary health institution in Ghana. The data addresses a need for more studies on viral associated respiratory tract infection.</p

Resting-State Multi-Spectrum Functional Connectivity Networks for Identification of MCI Patients

In this paper, a high-dimensional pattern classification framework, based on functional associations between brain regions during resting-state, is proposed to accurately identify MCI individuals from subjects who experience normal aging. The proposed technique employs multi-spectrum networks to characterize the complex yet subtle blood oxygenation level dependent (BOLD) signal changes caused by pathological attacks. The utilization of multi-spectrum networks in identifying MCI individuals is motivated by the inherent frequency-specific properties of BOLD spectrum. It is believed that frequency specific information extracted from different spectra may delineate the complex yet subtle variations of BOLD signals more effectively. In the proposed technique, regional mean time series of each region-of-interest (ROI) is band-pass filtered ( Hz) before it is decomposed into five frequency sub-bands. Five connectivity networks are constructed, one from each frequency sub-band. Clustering coefficient of each ROI in relation to the other ROIs are extracted as features for classification. Classification accuracy was evaluated via leave-one-out cross-validation to ensure generalization of performance. The classification accuracy obtained by this approach is 86.5%, which is an increase of at least 18.9% from the conventional full-spectrum methods. A cross-validation estimation of the generalization performance shows an area of 0.863 under the receiver operating characteristic (ROC) curve, indicating good diagnostic power. It was also found that, based on the selected features, portions of the prefrontal cortex, orbitofrontal cortex, temporal lobe, and parietal lobe regions provided the most discriminant information for classification, in line with results reported in previous studies. Analysis on individual frequency sub-bands demonstrated that different sub-bands contribute differently to classification, providing extra evidence regarding frequency-specific distribution of BOLD signals. Our MCI classification framework, which allows accurate early detection of functional brain abnormalities, makes an important positive contribution to the treatment management of potential AD patients

Altered Cerebellar-Cerebral Functional Connectivity in Geriatric Depression

Although volumetric and activation changes in the cerebellum have frequently been reported in studies on major depression, its role in the neural mechanism of depression remains unclear. To understand how the cerebellum may relate to affective and cognitive dysfunction in depression, we investigated the resting-state functional connectivity between cerebellar regions and the cerebral cortex in samples of patients with geriatric depression (n = 11) and healthy controls (n = 18). Seed-based connectivity analyses were conducted using seeds from cerebellum regions previously identified as being involved in the executive, default-mode, affective-limbic, and motor networks. The results revealed that, compared with controls, individuals with depression show reduced functional connectivity between several cerebellum seed regions, specifically those in the executive and affective-limbic networks with the ventromedial prefrontal cortex (vmPFC) and increased functional connectivity between the motor-related cerebellum seed regions with the putamen and motor cortex. We further investigated whether the altered functional connectivity in depressed patients was associated with cognitive function and severity of depression. A positive correlation was found between the Crus II–vmPFC connectivity and performance on the Hopkins Verbal Learning Test-Revised delayed memory recall. Additionally, the vermis–posterior cinglate cortex (PCC) connectivity was positively correlated with depression severity. Our results suggest that cerebellum–vmPFC coupling may be related to cognitive function whereas cerebellum–PCC coupling may be related to emotion processing in geriatric depression

Developmentally Regulated Sphingolipid Degradation in Leishmania major

Leishmania parasites alternate between extracellular promastigotes in sandflies and intracellular amastigotes in mammals. These protozoans acquire sphingolipids (SLs) through de novo synthesis (to produce inositol phosphorylceramide) and salvage (to obtain sphingomyelin from the host). A single ISCL (Inositol phosphoSphingolipid phospholipase C-Like) enzyme is responsible for the degradation of both inositol phosphorylceramide (the IPC hydrolase or IPCase activity) and sphingomyelin (the SMase activity). Recent studies of a L. major ISCL-null mutant (iscl−) indicate that SL degradation is required for promastigote survival in stationary phase, especially under acidic pH. ISCL is also essential for L. major proliferation in mammals. To further understand the role of ISCL in Leishmania growth and virulence, we introduced a sole IPCase or a sole SMase into the iscl− mutant. Results showed that restoration of IPCase only complemented the acid resistance defect in iscl− promastigotes and improved their survival in macrophages, but failed to recover virulence in mice. In contrast, a sole SMase fully restored parasite infectivity in mice but was unable to reverse the promastigote defects in iscl−. These findings suggest that SL degradation in Leishmania possesses separate roles in different stages: while the IPCase activity is important for promastigote survival and acid tolerance, the SMase activity is required for amastigote proliferation in mammals. Consistent with these findings, ISCL was preferentially expressed in stationary phase promastigotes and amastigotes. Together, our results indicate that SL degradation by Leishmania is critical for parasites to establish and sustain infection in the mammalian host