Corticosteroid-Sparing Effect of Chromoglycate Sodium and Nedocromil

The most appropiate management for bronchial asthma is the control of airway inflammation. Corticosteroids are the most effective anti-inflammatory drugs available, but they have a number of side effects; most of these are dose-dependent. In children, asthma control should be accomplished with low steroid doses possibly given by inhalation. In a double-bind placebo-controlled crossover study a group of children with mild to moderate asthma received NED 16 mg/day or BDP 400 μg/day. Values for FEV1, PEF, symptoms use ofbronchodilators overlapped, whereas bronchial hyper-responsiveness assessed by histamine bronchoprovocation challenge was better with BDP than NED. In another case, one boy with high bronchial hyper-reactivity assessed by provocation test with hypertonic solution, experienced a significant improvement only after 2 weeks of therapy with Deflazacort (2 mg/Kg/day) followed by 4 months on combined treatment with NED (16 mg/day) and BDP (300 μ/day). Authors conclude that NED could have a steroidsparing effect over long-term use

Does autonomic neuropathy play a role in erythropoietin regulation in non-proteinuric Type 2 diabetic patients?

Aims Erythropoietin (EPO)-deficient anaemia has been described in Type 1 diabetic patients with both severe autonomic neuropathy (AN) and proteinuria. This study was aimed at distinguishing between the effects of AN and nephropathy on haemoglobin and EPO levels in Type 2 diabetic patients at an early stage of diabetic nephropathy. Methods In 64 Type 2 diabetic patients (age 52 +/- 10 years, duration 10 +/- 9 years) without overt nephropathy and other causes of anaemia or EPO deficit, we assessed cardiovascular tests of AN, 24-h blood pressure (BP) monitoring, urinary albumin excretion rate (UAE), a full blood count, and serum EPO. Results Although the Type 2 diabetic patients with AN did not show differences in haemoglobin and EPO when compared with patients without AN, the presence of haemoglobin < 13 g/dl was associated with the presence of AN (chi(2)= 3.9, P < 0.05) and of postural hypotension (chi(2)= 7.8, P < 0.05). In a multiple regression analysis including as independent variables gender, body mass index, duration of diabetes, smoking, creatinine, 24-h UAE, 24-h diastolic BP, ferritin, erythrocyte sedimentation rate, and autonomic score, we found that the only variables independently related to haematocrit were autonomic score, ferritin and erythrocyte sedimentation rate. Finally, the physiological inverse relationship between EPO and haemoglobin present in a control group of 42 non-diabetic non-anaemic subjects was completely lost in Type 2 diabetic patients. The slopes of the regression lines between EPO and haemoglobin of the control subjects and the Type 2 diabetic patients were significantly different (t = 14.4, P < 0.0001). Conclusion This study documents an early abnormality of EPO regulation in Type 2 diabetes before clinical nephropathy and points to a contributory role of AN in EPO dysregulation

Gefitinib inhibits the ability of human bone marrow stromal cells to induce osteoclast differentiation: implications for the pathogenesis and treatment of bone metastasis.

Significant relief of bone pain in patients with bone metastases was observed in a clinical trial of the epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor gefitinib in breast cancer. Osteoclast activation and differentiation are regulated by bone marrow stromal cells (BMSC), a heterogeneous cell compartment that comprehends undifferentiated mesenchymal stem cells (MSC) and their specialized progeny. In this regard, we found that human primary BMSCs express immunoreactive EGFR. Expression of EGFR mRNA and protein was also demonstrated in two human, continuous MSC-like cell lines, HDS-1 and HDS-2 cells. Treatment of HDS cells with EGF produced a significant increase in the levels of activated EGFR which was not observed in the presence of gefitinib. A significant reduction in the basal levels of activation of the EGFR and of Akt was observed in HDS cells following treatment with gefitinib. Treatment of HDS cells with gefitinib produced a significant reduction in the levels of secreted macrophage colony-stimulating factor (M-CSF) and cell-associated receptor activator of NF-kappaB ligand (RANKL) in both cell lines, as assessed by using specific ELISA and Western blotting techniques. Finally, the ability to sustain the differentiation of pre-osteoclasts of conditioned medium from gefitinib-treated HDS cells was reduced by approximately 45% as compared with untreated HDS cells. These data have demonstrated for the first time that the EGFR regulates the ability of BMSCs to induce osteoclast differentiation and strongly support clinical trials of gefitinib in breast cancer patients with bone disease

Pharmacokinetic and metabolism determinants of fluoropyrimidines and oxaliplatin activity in treatment of colorectal patients

Fluoropyrimidines and oxaliplatin continued to be the mainstay of therapeutic regimens in the treatment of colorectal cancer (CRC). For this reason, pharmacokinetic and metabolism of these drugs were analyzed and the identification of accurate and validated predictive, prognostic and toxicity markers became necessary to develop an effective therapy adapted to the patient's molecular profile, while minimizing life-threatening toxicities. In this review, we discuss literature data, defining predictive and prognostic markers actually identified in the treatment of CRC. We analyzed predictive markers of fluoropyrimidines effectiveness, principally for 5-Fluorouracil (5-FU) and also for oral fluoropyrimidines, as thymidylate Synthase (TS), dihydropyrimidine dehydrogenase (DPD), orotate phosphoribosyl transferase (OPRT), methylenetetrahydrofolate reductase (MTHFR), deoxyuridine triphosphate nucleotidohydrolase (dUTPase), micro-satellite instability. DPD represent the more studied 5-FU toxicity marker, followed by TS and OPRT. Oxaliplatin effectiveness is principally regulated by nucleotide excision repair (NER) pathway, including excision repair cross-complementation group 1 (ERCC1), X-ray cross-complementing group 1 (XRCC1) and xeroderma pigmentosum group D (XDP). The major oxaliplatin toxicity marker is represented by glutathione S-transferase (GST). All these results are based principally on retrospective studies. The future challenge became to validate molecular markers and their association with clinical outcomes in prospective trials, refining technologic platforms and bioin-formatics to accommodate the complexity of the multifaceted molecular map that may determine outcome, and determining CRC patients most likely to benefit from therapeutic interventions tailored specifically for them

Automatic lung segmentation and quantification of aeration in computed tomography of the chest using 3D transfer learning

Background: Identification of lung parenchyma on computer tomographic (CT) scans in the research setting is done semi-automatically and requires cumbersome manual correction. This is especially true in pathological conditions, hindering the clinical application of aeration compartment (AC) analysis. Deep learning based algorithms have lately been shown to be reliable and time-efficient in segmenting pathologic lungs. In this contribution, we thus propose a novel 3D transfer learning based approach to quantify lung volumes, aeration compartments and lung recruitability. Methods: Two convolutional neural networks developed for biomedical image segmentation (uNet), with different resolutions and fields of view, were implemented using Matlab. Training and evaluation was done on 180 scans of 18 pigs in experimental ARDS (u2NetPig) and on a clinical data set of 150 scans from 58 ICU patients with lung conditions varying from healthy, to COPD, to ARDS and COVID-19 (u2NetHuman). One manual segmentations (MS) was available for each scan, being a consensus by two experts. Transfer learning was then applied to train u2NetPig on the clinical data set generating u2NetTransfer. General segmentation quality was quantified using the Jaccard index (JI) and the Boundary Function score (BF). The slope between JI or BF and relative volume of non-aerated compartment (SJI and SBF, respectively) was calculated over data sets to assess robustness toward non-aerated lung regions. Additionally, the relative volume of ACs and lung volumes (LV) were compared between automatic and MS. Results: On the experimental data set, u2NetPig resulted in JI = 0.892 [0.88 : 091] (median [inter-quartile range]), BF = 0.995 [0.98 : 1.0] and slopes SJI = −0.2 {95% conf. int. −0.23 : −0.16} and SBF = −0.1 {−0.5 : −0.06}. u2NetHuman showed similar performance compared to u2NetPig in JI, BF but with reduced robustness SJI = −0.29 {−0.36 : −0.22} and SBF = −0.43 {−0.54 : −0.31}. Transfer learning improved overall JI = 0.92 [0.88 : 0.94], P < 0.001, but reduced robustness SJI = −0.46 {−0.52 : −0.40}, and affected neither BF = 0.96 [0.91 : 0.98] nor SBF = −0.48 {−0.59 : −0.36}. u2NetTransfer improved JI compared to u2NetHuman in segmenting healthy (P = 0.008), ARDS (P < 0.001) and COPD (P = 0.004) patients but not in COVID-19 patients (P = 0.298). ACs and LV determined using u2NetTransfer segmentations exhibited < 5% volume difference compared to MS. Conclusion: Compared to manual segmentations, automatic uNet based 3D lung segmentation provides acceptable quality for both clinical and scientific purposes in the quantification of lung volumes, aeration compartments, and recruitability

Automatic Lung Segmentation and Quantification of Aeration in Computed Tomography of the Chest Using 3D Transfer Learning

Background: Identification of lung parenchyma on computer tomographic (CT) scans in the research setting is done semi-automatically and requires cumbersome manual correction. This is especially true in pathological conditions, hindering the clinical application of aeration compartment (AC) analysis. Deep learning based algorithms have lately been shown to be reliable and time-efficient in segmenting pathologic lungs. In this contribution, we thus propose a novel 3D transfer learning based approach to quantify lung volumes, aeration compartments and lung recruitability. Methods: Two convolutional neural networks developed for biomedical image segmentation (uNet), with different resolutions and fields of view, were implemented using Matlab. Training and evaluation was done on 180 scans of 18 pigs in experimental ARDS (u2NetPig) and on a clinical data set of 150 scans from 58 ICU patients with lung conditions varying from healthy, to COPD, to ARDS and COVID-19 (u2NetHuman). One manual segmentations (MS) was available for each scan, being a consensus by two experts. Transfer learning was then applied to train u2NetPig on the clinical data set generating u2NetTransfer. General segmentation quality was quantified using the Jaccard index (JI) and the Boundary Function score (BF). The slope between JI or BF and relative volume of non-aerated compartment (SJI and SBF, respectively) was calculated over data sets to assess robustness toward non-aerated lung regions. Additionally, the relative volume of ACs and lung volumes (LV) were compared between automatic and MS. Results: On the experimental data set, u2NetPig resulted in JI = 0.892 [0.88 : 091] (median [inter-quartile range]), BF = 0.995 [0.98 : 1.0] and slopes SJI = 120.2 {95% conf. int. 120.23 : 120.16} and SBF = 120.1 { 120.5 : 120.06}. u2NetHuman showed similar performance compared to u2NetPig in JI, BF but with reduced robustness SJI = 120.29 { 120.36 : 120.22} and SBF = 120.43 { 120.54 : 120.31}. Transfer learning improved overall JI = 0.92 [0.88 : 0.94], P &lt; 0.001, but reduced robustness SJI = 120.46 { 120.52 : 120.40}, and affected neither BF = 0.96 [0.91 : 0.98] nor SBF = 120.48 { 120.59 : 120.36}. u2NetTransfer improved JI compared to u2NetHuman in segmenting healthy (P = 0.008), ARDS (P &lt; 0.001) and COPD (P = 0.004) patients but not in COVID-19 patients (P = 0.298). ACs and LV determined using u2NetTransfer segmentations exhibited &lt; 5% volume difference compared to MS. Conclusion: Compared to manual segmentations, automatic uNet based 3D lung segmentation provides acceptable quality for both clinical and scientific purposes in the quantification of lung volumes, aeration compartments, and recruitability

Atopic dermatitis and atopic march: which link?

There is a long standing debate on the atopic march in childhood. The natural progression of allergic manifestations may be considered as comorbidities, which occur more frequently in a specific evolutive age. On the other hand, the natural history of allergies in children may follow trajectories that may be heterogeneous. The effects of atopic march in clinical practice have also been reported

Implementing anti-epidermal growth factor receptor (EGFR) therapy in metastatic colorectal cancer: challenges and future perspectives

Epidermal growth factor receptor (EGFR) inhibitors are valuable therapeutics in metastatic colorectal cancer (mCRC). Anti-EGFR monoclonal antibodies (MoAbs), such as cetuximab or panitumumab, in combination with chemotherapy are effective treatment options for patients with RAS and BRAF wild-type mCRC. Nevertheless, several issues are still open concerning the optimal use of anti-EGFR drugs in the continuum of care of mCRC. Novel approaches for increasing the efficacy of anti-EGFR therapies include better molecular selection of EGFR-dependent mCRC, intensification of chemotherapy, combination of anti-EGFR MoAbs and immune checkpoint inhibitors, and reintroduction of EGFR blockade or 'rechallenge' in selected patients who have previously responded to anti-EGFR MoAb therapy. An extensive translational research program was conducted in the Cetuximab After Progression in KRAS wIld-type colorectal cancer patients-Gruppo Oncologico dell' Italia Meridionale (CAPRI-GOIM) study with the aims of determining which subgroups of patients could benefit from the continuous inhibition of EGFR, from evaluating the role of liquid biopsy-based and its concordance with tissue-based molecular testing, and from investigating novel potential mechanisms of resistance to anti-EGFR therapies. In this review, we summarize the translational and clinical findings of the CAPRI-GOIM program in the context of the current knowledge of therapeutic strategies and of ongoing research on more appropriate uses of anti-EGFR therapies in RAS and BRAF wild-type mCRC patients

Excess path delays from sentinel interferometry to improve weather forecasts

A synthetic aperture radar can offer not only an accurate monitoring of the earth surface deformation, but also information on the troposphere, such as the total path delay or the columnar water vapor at high horizontal resolution. This can be achieved by proper interferometric processing and postprocessing of the radar interferograms. The fine and unprecedented horizontal resolution of the tropospheric products can offer otherwise unattainable information to be assimilated into numerical weather prediction models, which are progressively increasing their resolving capabilities. A number of tricks on the most effective processing approaches, as well as a novel method to pass from multipass differential interferometry products to absolute tropospheric columnar quantities are discussed. The proposed products and methods are assessed using real Sentinel-1 data. The experiment aims at evaluating the accuracy of the derived information and its impact on the weather prediction skill for two meteorological events in Italy. The main perspective of the study is linked to the possibility of exploiting interferometric products from a geosynchronous platform, thus complementing the inherent high resolution of SAR sensors with the required frequent revisit needed for meteorological applications