WHO tri-regional policy dialogue seeks solutions to challenges facing international mobility of health professionals The study was approved by Institutional Review Boards of Jeroen Bosch Hospital, Bernhoven Hospital and Radboud University Medical CenterThe diagnostic test for COVID-19 infection is a reverse transcription polymerase chain reaction (RT-PCR) test. However, there has been a severe shortage of test-kits worldwide and furthermore, laboratories in most countries have struggled to process the available tests within a reasonable time-frame. While efforts to increase the capacity for RT-PCR testing have been underway, healthcare workers attempting to triage symptomatic patients have turned to imaging in the form of chest radiography or CT. Imaging is part of a triage to assess pulmonary health and route patients to the appropriate parts of the healthcare system. There are several strategies and flow charts in diagnosing and ruling out COVID-19 and chest radiography and / or CT have been widely used as part of the initial screening process    .While many countries have experienced difficulties in allocating scarce resources throughout the COVID-19 pandemic, countries such as those in the developing world with economic, infrastructural, governmental and healthcare problems (‘resource-constrained’) are particularly at risk. In resource-constrained settings, the COVID-19 pandemic could have consequences far more severe than we have already seen in industrialised countries. The WHO reports that as of April 15 outbreaks were confirmed in 45 African countries, describing 10,759 cases with 520 deaths . Given the lack of access to medical care and the low availability of RT-PCR tests across the African continent, it is likely that the true numbers are much higher. The strategy in these regions must focus heavily on detection and reduction of transmission through effective isolation and quarantine processes.Chest radiography (CXR) is a fast and relatively inexpensive imaging modality which is available in many resource-constrained healthcare settings. Unfortunately, there is a severe shortage of radiological expertise in these regions to allow for precise interpretation of such images . An AI system may be a helpful tool as an adjunct to radiologists or, in the common case that radiological expertise is not available, for the medical team  . Previous work in the related task of tuberculosis (TB) detection on CXR    has demonstrated that software can perform at the level of an expert radiologist at the task of TB identification. In this study we evaluate the performance of an available  artificial intelligence (AI) system for the detection of COVID-19 pneumonia on CXR.Materials and MethodsDataThis study was approved by the Institutional Review Boards of Jeroen Bosch Hospital (‘s Hertogenbosch, The Netherlands), Bernhoven Hospital (Uden, The Netherlands) and Radboud University Medical Center (Nijmegen, The Netherlands). Informed written consent was waived, and data collection and storage were carried out in accordance with local guidelines.Artificial intelligence system for X-ray interpretationCAD4COVID-XRay is a deep-learning based AI system for the detection of COVID-19 characteristics on frontal chest radiographs. The software was developed by Thirona (Nijmegen, The Netherlands) and provided for this study. Some authors are employees (RP, AM, JM) or consultant (BvG) of Thirona, the other authors had control of inclusion of any data and information in this study. CAD4COVID-Xray is based on the CAD4TB v6 software , which is a commercial deep-learning system for the detection of tuberculosis on chest radiographs. As pre-processing steps, the system uses image normalisation  and lung segmentation using a U-net . This is followed by patch-based analysis using a convolutional neural network and an image level classification using an ensemble of networks.The system was re-trained, firstly on a pneumonia dataset , acquired prior to the COVID-19 outbreak. This data is publicly available and has been fully anonymised. It is known to come from a single centre but details of the X-ray system(s) are not available. This dataset includes 22,184 images of which 7,851 were labelled normal and 5,012 were labelled as pneumonia. The remainder had other abnormalities inconsistent with pneumonia. A validation set of 1500 images (500 per label, equally split between PA and AP images) was held out and used to measure performance during the training process. The purpose of re-training using this data was to make the system sensitive and specific to pneumonia in general, since large numbers of COVID-19 images are difficult to acquire at present. To fine-tune the system for detection of COVID-19 specifically, an additional training set of anonymised CXR images was acquired from Bernhoven Hospital comprising 416 images from RT-PCR positive subjects and 191 images from RT-PCR negative subjects. These were combined with 96 COVID-19 images from other institutes and public sources and 291 images from Radboud University Medical Center from the pre-COVID-19 era (used to increase numbers of negative samples). This dataset of 994 images was used to re-train the system a final time, holding 40 images out for validation (all from Bernhoven Hospital, equally split between positive and negative and PA/AP). This dataset comprised all RT-PCR confirmed data available to us (excluding the test set) with the addition of negative data to balance the class sizes. The system takes approximately 15 seconds to analyse an image on a standard PC.The test set was selected from CXR images from the Jeroen Bosch Hospital (’s-Hertogenbosch, The Netherlands) acquired from COVID-19 suspected subjects presenting at the emergency department with respiratory symptoms between March 4 and April 6, 2020. All patients underwent laboratory measurements, CXR imaging and RT-PCR testing (Thermo Fischer Scientific, Bleiswijk, The Netherlands).The imaging data included both standard radiographs (posteroanterior (PA) and lateral projection) of the chest (Digital Diagnost, Philips, Eindhoven, The Netherlands), of which only the PA images were selected, as well as the anteroposterior (AP) projections obtained with a mobile system (Mobile Diagnost, Philips, Eindhoven, The Netherlands). Of all 827 frontal images, a single image per patient with a RT-PCR result available was selected (n = 555).Where multiple CXR images were available for a patient the best quality image, acquired for diagnostic purposes was selected. This selection contained only one image of a minor (age 4), which was included since the AI software is intended to work on minors age 4 and upwards. In total 87 images that did not display the entire lungs or which were acquired for non-diagnostic purposes such as checking tube positioning were excluded. The patient characteristics of the remaining 468 images are detailed in Table 1.Table 1: Properties of training, validation and test sets. Age, gender and orientation are not known for all training cases due to anonymization of the datasets at their source.Multi-reader studyThe test set was scored by six readers (AK: Chest radiologist with five years of experience, MK: Chest radiologist with 20 years of experience, CSP: Chest radiologist with more than 20 years of experience, MR: Radiologist with 24 years of experience, ETS: Chest radiologist with more than 30 years of experience, SS: Chest radiologist with six years of experience). Readers assigned each image one of the following categories.(0) Normal: No finding (1) Abnormal but no lung opacity consistent with pneumonia(2) Lung Opacity consistent with pneumonia (unlikely COVID-19)(3) Lung Opacity consistent with pneumonia (consistent with COVID-19)Readers could also mark images as unreadable. All readers assessed the images independently, fully blinded to other reader opinions, clinical information and RT-PCR results.Reader consensus was used to evaluate the AI system against a radiological reference standard and to provide an overview of the pulmonary abnormalities of the test set from a radiological viewpoint. To create a consensus among readers, the most frequently chosen score for an image was selected. Where there was a tie of frequencies the higher score was selected.Statistical methodsPerformance of the AI system was assessed by generation of a receiver operating characteristic (ROC) curve from the AI system scores. Area under the ROC curve (AUC) is reported. Similarly, reader performance was evaluated by thresholding at different score levels to generate ROC points.Confidence intervals (95 per cent) on the ROC curve and on the reader sensitivity / specificity points were generated by bootstrapping .For each reader sensitivity value, the corresponding specificity and the specificity of the AI system at that sensitivity setting are computed. A statistically significant difference is determined by means of the McNemar test. The resulting p-values are reported in each case (p < 0.05 was considered significant).Additionally, the performance of the AI system and each reader was measured against a consensus radiological reference standard of the remaining five readers. For creation of an ROC curve, the reference standard is required to be binary. This was achieved by setting the reference standard at 1 for images rated consistent with COVID-19 and at 0 for images with any other consensus-score.Positive and negative predictive values (PPV and NPV) were calculated for all readers and for the consensus reading using a reference standard of RT-PCR results. We defined three operating points for The AI system at sensitivities of 60 per cent, 75 per cent and 85 per cent, respectively, and computed the same metrics.ResultsAny image considered unreadable by any of the readers was excluded from analysis. Of the 468 images, 454 were successfully read by all six readers. Readers were not required to specify reasons for rejection of images, however, where comments were provided these related to poor image quality caused by weak inspiration or incorrect patient positioning. To provide an overview of the content of the test set from a radiological point of view, the consensus of all six readers was established on the remaining 454 images. This consensus labels 117 cases as normal (0), 94 cases as containing abnormalities other than pneumonia (1), 26 cases as pneumonia not consistent with COVID-19 (2) and 217 cases as consistent with COVID-19 pneumonia (3). These numbers indicate the diversity of pathology in the test set.The AI system was applied successfully to all 454 cases. Figure 1 shows examples of the AI system heat maps of a RT-PCR positive patient and a RT-PCR negative patient.Figure 1a: Top Row: 74 year old male with positive RT-PCR test for SARS-COV2 viral infection. (A) Frontal chest x-ray (B) The artificial intelligence (AI) system heatmap overlaid on the image showing the pneumonia related features. The AI system score for this subject is 99.8. Bottom Row: 30 year old male with negative RT-PCR test for SARS-COV2 viral infection. (C) Frontal chest x-ray (D) The artificial intelligence (AI) system heatmap overlaid on the image. The The AI system score for this subject is 0.2.Figure 1b: Top Row: 74 year old male with positive RT-PCR test for SARS-COV2 viral infection. (A) Frontal chest x-ray (B) The artificial intelligence (AI) system heatmap overlaid on the image showing the pneumonia related features. The AI system score for this subject is 99.8. Bottom Row: 30 year old male with negative RT-PCR test for SARS-COV2 viral infection. (C) Frontal chest x-ray (D) The artificial intelligence (AI) system heatmap overlaid on the image. The The AI system score for this subject is 0.2.The ROC results for all six readers and the AI system using RT-PCR results as the reference standard are depicted in Figure 2. The AI system achieved an AUC of 0.81. In most regions of the ROC curve the system performed better than, or at the same level as, the readers. Clusters of points from radiological readers are seen at sensitivities of approximately 60 per cent, 75 per cent and 85 per cent. While the ROC curve indicates specificity at all sensitivity levels, we identified three particular operating points in line with these sensitivities where reader points are clustered. At 60 per cent sensitivity, the AI system obtains a specificity of 85 per cent (95 per cent CI [79-90 per cent]), at 75 per cent sensitivity the specificity is 78 per cent (95 per cent CI [66-83 per cent]), while at a setting of 85 per cent sensitivity the specificity decreases to 61 per cent (95 per cent CI [48-72 per cent]).Figure 2: The ROC curve for the artificial intelligence (AI) system and points for each reader (point locations are specified in the Figure legend). Reference standard is RT-PCR test result. 95% confidence intervals are shown as a shaded area for the ROC curve and cross-hairs for each reader point. AI System operating points discussed in the text are shown at sensitivities of 60%, 75% and 85%. AUC = Area under receiver operating characteristic curve.Table 2 compares the AI system and reader performance at sensitivity values fixed for the readers’ ROC points. The system outperformed all readers at their highest sensitivity for detection of COVID-19 characteristics. At intermediate sensitivity settings, the system statistically outperformed reader three, while no reader was statistically better than the system. At the lowest sensitivity setting, only reader two could outperform the system (p = 0.04), while the system continued to outperform reader three (p = 0.01).We additionally compared each reader and the AI system against the radiological reference standard set by the consensus of the remaining 5 readers. These results are illustrated in Figure 3. The AUC of the AI system against the radiological reference standards was generally slightly higher than against the RT-PCR test results (with the exception of the fifth curve in Figure 3). In each plot the system performance was close to the individual reader, with the exception of reader 2 who achieved slightly better results compared to the consensus of the other five readers.Figure 3: ROC curves for the artificial intelligence (AI) system and each reader individually. Reference standard in each case is the consensus reading of the remaining 5 readers. 95% confidence intervals are shown as a shaded area for the ROC curve. AUC = Area under receiver operating characteristic curve.Results of the analysis of PPV and NPV are shown in Table 3. The AI operating points were selected at sensitivities of 60 per cent, 75 per cent and 85 per cent coinciding with the observed clusters of points from the radiological readers at these locations in the ROC curve (Figure 1). At low and intermediate sensitivity operating points AI has a similar performance to the readers (using the related cut-off point for reader scores) in terms of PPV and NPV. On the other hand, at high sensitivity AI outperformed the six readers both in terms of NPV and PPV.Table 3: Positive Predictive Values (PPV) and Negative Predictive Values (NPV) for each reader, for the artificial intelligence (AI) system, and for the consensus reading. The three possible cut-off points for reader scores are used while three operating points for the AI system are defined at 60 per cent, 75 per cent and 85 per cent. These correspond to clusters of radiological reader points on the ROC curve. Reference standard is RT-PCR results.DiscussionIn this study, we evaluated the performance of an AI system to detect abnormalities related to COVID-19 chest radiographs on an independent test set and compared it to radiologist readings. The external test set used to evaluate the AI system was from a hospital system different from that used to train and validate the AI system. The exams in the test set were representative of the CXR studies obtained during the peak of the COVID-19 epidemic in The Netherlands and were not selected to exclude other abnormalities. Based on the reader consensus, 120 of these images had abnormalities not consistent with COVID-19, 117 were completely normal and the remaining 217 had abnormalities consistent with COVID-19. The AI system performance for detection of COVID-19 was compared with six independent readers and was found to be comparable or even better at high sensitivity operating points. In the clinical setting, the PPV and NPV of AI may be considered more useful, indicating the likelihood of COVID-19 given a positive or negative result from the system . Our results show that at a fixed operating point (sensitivity of 75 per cent) the AI system has a PPV of 77 per cent and NPV of 76 per cent. This result is comparable to performance using the consensus of all six readers (PPV=72 per cent, NPV=78 per cent).The results achieved by the AI system compared to radiologist readings are noteworthy given the fact that the presentation of COVID-19 pneumonia on CXR can be highly variable ranging from peripheral opacifications only to diffuse opacifications making differentiation from other diseases challenging   . Chest radiographs may be normal initially or in mild disease, however Wong et al. showed that of all patients with COVID-19 requiring hospitalisation, 69 per cent had an abnormal chest radiograph at admission . During hospitalisation, 80 per cent showed chest X-ray abnormalities, which were most extensive 10-12 days after symptom onset . Frequent findings related to COVID-19 on chest X-ray are ground glass densities, diffuse air space disease, bilateral lower lobe consolidations and peripheral air space opacities, predominantly dorso-basal in both lungs  . Pleural effusions, lung cavitation and pneumothorax may occur but are relatively rare .To improve the performance of the AI system for COVID-19 a larger training set of radiographs is needed. Improvements may also be obtained by combining radiography analysis with clinical and laboratory findings.In future work, the role of AI in management or triage of patients in the COVID-19 pandemic should be investigated, taking all related patient information and the experience level of the healthcare professionals interpreting the radiographs into account.Our study has several limitations. First, the test set comes from a single institution, which may not be representative of data from other centres. Second, the number of COVID-19 (RT-PCR positive) images in the training set of the system was relatively small (512 images), relative to the number of labelled pneumonia (non-COVID-19) images (5,012) and the system evaluated only frontal X-rays. Also, the test set was not ideally suited to test the ability of the AI system to differentiate COVID-19 from non-COVID-19 pneumonia because the test set had been obtained during the peak of the pandemic and the number of non-viral pneumonia cases (according to the reader consensus) was relatively small. We used the RT-PCR as the reference standard, but RT-PCR has limited sensitivity for COVID-19 infection (71 per cent) . This suggests that there may be subjects in our test set with indications of COVID-19 on chest radiography but with a negative RT-PCR result.In summary, we evaluated an AI system for detection of COVID-19 characteristics on frontal chest radiographs. The AI system was comparable to six independent readers. The tool is made available pro bono on the manufacturer’s website, to be of benefit in public health surveillance and response systems worldwide and may provide support for radiologists and clinicians in chest radiograph assessment as part of a COVID-19 triage process.References:1. Worldometers Corona Virus,” 2020. [Online]. Available: https://www.wordlometers.info/coronavirus/. Google Scholar2. W. Yang, A. Sirajuddin, X. Zhang, G. Liu, Z. Teng, S. Zhao, M. Lu, “The role of imaging in 2019 novel coronavirus pneumonia (COVID-19),” European Radiology, vol. April 15, pp. 1-9, 2020. Google Scholar3. G. D. Rubin, C. J. Ryerson, L. B. Haramati, N. Sverzellati, J. P. Kanne, S. Raoof, N. W. Schluger, A. Volpi, J.-J. Yim, I. B. K. Martin, D. J. Anderson, C. Kong, T. Altes, A. Bush et al, “The Role of Chest Imaging in Patient Management during the COVID-19 Pandemic: A Multinational Consensus Statement from the Fleischner Society,” Radiology, vol. Apr 7, 2020. Google Scholar4. M. P. Cheng, J. 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Google ScholarSource: RSNA Read Article MaxiVision Eye Hospitals launches “Mucormycosis Early Detection Centre” News Radiology The missing informal workers in India’s vaccine story Share AIBernhoven HospitalCAD4COVID-XRaychest radiographsCOVID-19Jeroen Bosch HospitalRadboud University Medical CenterRT-PCR testing Comments (0) Heartfulness group of organisations launches ‘Healthcare by Heartfulness’ COVID care app Related Posts Phoenix Business Consulting invests in telehealth platform Healpha Indraprastha Apollo Hospitals releases first “Comprehensive Textbook of COVID-19” Menopause to become the next game-changer in global femtech solutions industry by 2025 By EH News Bureau on May 11, 2020 CAD4COVID-XRay can identify characteristics of COVID-19 on chest radiographs with performance comparable to six readers Add Comment
Among their many roles as message couriers and gene regulators, microRNA molecules also help control the repair of damaged DNA within cells, Dana-Farber Cancer Institute and Harvard Medical School scientists report in the May issue of Nature Structural & Molecular Biology.The finding not only demonstrates the unexpected versatility of microRNA (miRNAs) in the life of cells but also may lead to new tests for determining a tumor’s aggressiveness and likely response to different therapies. Because radiation and chemotherapy kill cancer cells by damaging their genetic material, knowledge of the DNA repair mechanism may suggest novel solutions to the problem of drug resistance, in which tumors develop the ability to withstand drugs that initially were effective against them.“MicroRNAs are gaining an increasing amount of attention in cancer research, but there hasn’t been any evidence that they play a role in DNA repair,” says Dipanjan Chowdhury of Dana-Farber and assistant professor of radiation oncology at Harvard Medical School. Chowdhury is senior author of the paper and the co-corresponding author with Judy Lieberman, professor of pediatrics at Harvard Medical School and the Immune Disease Institute in Boston. “This study is the first to provide that evidence.”To find out whether miRNAs are involved in DNA repair, Chowdhury and his colleagues collected several sets of mature blood cells, which have a low ability to repair DNA damage, and identified the types of miRNA within them. They found that different types of blood cells had small sets of miRNAs in common — an overlapping “miRNA signature.” One of the strongest links among the cell groups was an miRNA known as miR-24. The investigators discovered that the cells had high levels of miR-24, which caused a slowdown in production of a DNA-mending protein called H2AX, impacting the efficiency of DNA repair.The discovery raises the issue of why a cell might want to give its DNA repair crew a break from time to time. Because DNA contains the operating instructions for cell division (and other processes), it would seem prudent for cells to be constantly ready to fix broken DNA, much as an electric power company has repair teams always available. In fact, however, during the “resting phase” of cell division — when genes involved in division are inactive — repairs are unnecessary. Hence the need for molecules like miRNAs to temporarily quiet the repair response.The implications of the discovery for the treatment of cancer and other genetically caused diseases are compelling, says Chowdhury. As researchers identify additional miRNAs involved in DNA repair, tumors may one day be routinely analyzed for miRNA content. “A tumor’s miRNA profile may serve as a marker for how aggressive the malignancy is likely to be, and how vulnerable it will be to DNA-damaging agents,” Chowdhury adds.The research may also result in new forms of therapy. Drugs that impede cancer cells’ ability to repair their DNA could make such cells more vulnerable to radiation and chemotherapy. Recent studies in primates have shown that some pharmacological compounds can alter miRNA activity. Such compounds could potentially reverse tumors’ resistance to conventional therapies.The co-lead authors of the study are Ashish Lal and Francisco Navarro of the Immune Disease Institute and Yunfeng Pan of Dana-Farber. Co-authors include Derek Dykxhoorn of the Immune Disease Institute, Lisa Moreau of Dana-Farber, and Eti Meire and Zvi Bentwich of Rosetta Genomics, in Rehovot, Israel.The research was supported by grants from the National Institutes of Health and GlaxoSmithKline, and an award from the Claudia Adams Barr Foundation.
David Smith has worked in a number of leadership roles for the Kansas City, Kan., school district for the past 13 years.The Shawnee Mission Board of Education tonight is expected to approve the hiring of David Smith, who has led Kansas City, Kansas Public Schools public affairs operations for several years, as the district’s new Chief Communications Officer.Smith moved to Kansas City in the late 1990s to become the Assistant Superintendent for Communications in the Kansas City, Missouri School District. Prior to that role, he had worked in roles for the Kettering Foundation and for the Annenberg Institute for School Reform at Brown University. He also worked as the Vice-President for Education at the Partnership for Children, which produced annual analyses of school performances for districts in the metro area.Smith, who has been with KCKPS for the past 13 years, holds degrees from Yale University and Yale Divinity School, and started his career as a middle school teacher.Incoming Superintendent Michael Fulton said Smith’s background would make him a valuable addition to the administration.“David brings a wealth of experience in school communications and will lead the district’s efforts to ensure the SMSD community is informed and engaged with our work,” Fulton said.For his part, Smith cited the district’s history of excellent outcomes as part of the appeal.“I am excited to join the dynamic team at the Shawnee Mission School District,” said Smith said. “The district’s long tradition of excellence, along with Dr. Fulton’s passion for continuous improvement in a student-focused environment, makes this an exciting place for me to learn, grow and contribute.”Pending approval by the board at tonight’s meeting, Smith would begin his new role July 5.
The signing came a day before the October 25 deadline specified in the bidding terms. It took place in the presence of Prime Minister General Prayuth Cha-o-cha, emphasising the government’s hope that the railway will bolster development on the east coast.The 1 435 mm gauge route with nine stations will start at Don Mueang Airport to the north of Bangkok, running south to Bang Sue Grand Station and Makkasan, from where it will use the existing airport rail link to Suvarnabhumi Airport east of the city. It would then continue along the alignment of SRT’s metre-gauge eastern railway to Chachoengsao, Chon Buri, Si Racha and Pattaya before terminating at U-Tapao Airport in Rayong province. Trains would run at up to 160 km/h on the urban section and 250 km/h elsewhere, reducing the current journey of 4 h by road to 45 min.The 50-year PPP agreement provides for commercial development on SRT-owned land in addition to the construction and operation of the railway. The government would contribute 117·2bn baht to the estimated total cost of 224·5bn baht, and the assets would revert to the state at the end of the concession.The government’s Eastern Economic Corridor board has endorsed a plan to accelerate the handover of the required construction sites, and work is scheduled to start in early 2021 for opening in 2023.‘It is an historic moment in Thailand that the private sector signed the PPP agreement with the public sector to promote this international mega construction project’, said CP Group CEO Suphachai Chearavanont, thanking ‘all strategic alliances both domestically and internationally’ including Japan Bank for International Co-operation, China Development Bank, and the ambassadors of China, Japan and Italy. THAILAND: The public-private partnership agreement for the construction of a 220 km/h fast rail link between three airports around Bangkok was signed by State Railway of Thailand and the Eastern High-Speed Rail Link Three Airports Co Ltd consortium on October 24.The consortium is led by Charoen Pokphand Group and includes China Railway Construction Corp, Bangkok Expressway & Metro, Italian-Thai Development and CH Karnchang.#*#*Show Fullscreen*#*#
Some of the stories in Friday’s newspapers involving the area’s clubs…Tottenham have again been tipped to move for Fulham star Ryan Sessegnon this summer.Spurs have long been strongly interested in Sessegnon, who has been linked with several other clubs.AdChoices广告His contract at Craven Cottage runs until next year and The Sun suggest bids for him will start at £25m and that Spurs will look to agree a deal.It comes amid reports that relegation would lead to several Fulham players leaving the club.There continues to be speculation over Sessegnon’s futureThere is also speculation about who will be managing Fulham next season.Several newspapers have picked up on a story by i News that the Whites want to appoint former Huddersfield boss David Wagner.Meanwhile, Chelsea are considering appointing Frank Lampard or Wolves boss Nuno Espirito Santo this summer, The Sun claim.The newspaper previously tipped Zinedine Zidane to replace under-pressure head coach Maurizio Sarri at Stamford Bridge.With Zidane having instead returned to Real Madrid, The Sun now say Nuno and Chelsea legend Lampard are in the frame.Lampard – the Blues’ all-time record goalscorer – is currently manager of Derby County, while Nuno’s Wolves side have impressed in the Premier League.The Sun say Chelsea owner Roman Abramovich is reluctant to sack Sarri before the end of the season but that there are doubts over whether the Italian is the right man for the job. Follow West London Sport on TwitterFind us on Facebook
7 September 2010 New South African film Hopeville spreads the message that even one person, when they have the courage to take action, can make a big difference in many lives. Shot in Waterval Boven in Mpumalanga province and featuring a stellar cast of local actors, Hopeville is directed by John Trengrove and produced by Curious Pictures, with music by producer/composer Murray Anderson. The film opened at 13 Nu Metro and 20 Ster-Kinekor theatres countrywide, as well as a handful of independent cinemas, on 3 September. Free high-resolution photos and professional feature articles from Brand South Africa’s media service. A new start Amos, a reformed alcoholic, is a man looking for a new start. When he arrives in the fictional town of Hopeville with his estranged son, who has been put into the custody of his father after his mother dies unexpectedly, he faces a tough battle with corrupt officials and an apathetic community. As part of his custody agreement, Amos has promised to encourage his son’s promising swimming career, but the pool in Hopeville contains only garbage and stagnant puddles of water. Amos decides to clean it up for his son’s sake, and the project soon captures the attention and goodwill of the community, who begin to pitch in. The mayor, however, is not pleased because he and his cronies have decided to build a liquor store on the land, and Amos faces fierce resistance, intimidation and threats. He is going to need all his courage, and the support of the residents, if he is to complete the restoration of the pool. A restrained, dignified performance by lead actor Themba Ndaba (Generations) as Amos contrasts with the over-the-top bad guy portrayals of local comedian Desmond Dube (Hotel Rwanda) as the corrupt mayor, and audience favourite Fana Makoena (Generations) as his shady sidekick. “Amos’s journey will touch a lot of people, as we see somebody trying to put things right,” said Ndaba. Others in the cast include Terry Pheto of Oscar-winning Tsotsi fame, Nat Singo (Beat the Drum) as Amos’s son Themba, Jonathan Pienaar (The Lab), and the ever-popular Leleti Khumalo (Invictus, Cry, the Beloved Country). Hopeville tackles contemporary issues of great relevance to South Africans, such as service delivery, social and moral values, crime and corruption, and the relationships of family and friends.Television spin-off Hopeville was inspired by the 2009 television series of the same name, also produced by Curious Pictures. The series producers considered more than 70 locations before settling on the scenic town of Waterval Boven, sitting on the very edge of the escarpment between the high- and low-lying areas of Mpumalanga. The town is popular for fly-fishing, rock-climbing and hiking, and features a number of historical and national monument sites dating back to the days of the Nederlandsche Zuid-Afrikaansch Spoorweg-Maatschappij, which operated in the late 19th century. The film’s cast is largely the same as that of the series, as is the story. NGO Heartlines, in partnership with SABC Education, commissioned the series as part of its work of using television and film to help South Africans strive towards the values of humility, compassion, responsibility, perseverance, and other positive goals, in their lives. The six-episode series aired for the first time in March 2009, and was re-broadcast in September that year. Recently it was nominated for competition in the Rose d’Or, a prestigious international festival featuring the best in entertainment television. The competition takes place every year in Lucerne, Switzerland. Hopeville is one of 110 shows which made it through to the competition round, out of 515 entries submitted. It will compete in the Drama and Mini-series category. Previous winners of the top prize, the Golden Rose, include The Muppet Show (1977), Mr Bean (1990), Little Britain (2005) and The Eternity Man (2009). “What I love about Heartlines’ work is that they allow us to talk about social issues, which opens up dialogues between different people,” said Jonathan Pienaar, who plays Fred Palmer in the series and film. Beautifully filmed and deftly acted, Hopeville will leave audiences inspired to imitate Amos’s actions and do some good in their communities, even if it is something small, without waiting for someone else to step in. First published by MediaClubSouthAfrica.com – get free high-resolution photos and professional feature articles from Brand South Africa’s media service. MediaClubSouthAfrica
India Today NEWS PICKModi gets his way, Joshi quits BJP BCCI boss caught in Jagan web? Paris won, London next for Sania-Hesh Happy birthday Shilpa! Rare childhood pics of Bollywood queen and her family What’ll Nano look like in 5 yrs?Days after changing the fortunes of bottom-enders in the first four seasons of the Indian Premier League (IPL) to the champions of the latest edition, Kolkata Knight Riders (KKR) Gautam Gambhir batted for a heavy penalty for the franchises who were unable to control the conduct of their players.”Somewhere down the line franchises need to control these things. A certain player from a certain team does these things, the franchise needs to be fined and it has to be fined heavily,” Gambhir said in an interview with Headlines Today on Friday.Royal Challengers Bangalore’s Luke Pomersbach had been accused of molestation by an American national during the just concluded IPL 5 tournament.The southpaw put up a strong defence of the IPL and the Board of Control for Cricket in India (BCCI), saying, “It is the responsibility of the franchise to control its players. BCCI can’t appoint one person each to keep a watch over every player.””Players who have a history of binge drinking and have got into trouble in the past, franchises should impose a curfew on them and they should be sent back to their rooms,” he said.The IPL also faced allegations of spot-fixing and black money leading some, including BJP MP Kirti Azad, to demand a ban on the popular Twenty-20 tournament. However, Gambhir put up a stout defence of the BCCI shifting the onus to franchises.advertisement”We keep blaming the BCCI and the IPL for all these things. A lot of these things can be sorted out if the franchise is strong enough. Whatever we sign for is given, and nothing is given under the table,” he said.Answering the parliamentarian’s demand for a ban, Gambhir said, “I am sure there are a number of other issues for Parliament to debate than the IPL.”Gambhir admitted that he would love to be a Test captain.”I would relish the opportunity to be Test captain. Who doesn’t want to? But captaincy won’t change my passion for the game,” the Delhi batsman said.He said that his effort was to make KKR a team known for its on field achievements. “In the last three years, KKR has been known too much for what happened off the cricket field. I wanted to change that,” he said.Gambhir said after the kind of receptions he received at the Eden Gardens, he now considers himself a Kolkata boy. However, the one thing that Gambhir cannot do is dance for KKR co-owner, actor Shah Rukh Khan.”The one thing I cannot do is dance for Shah Rukh Khan. He has succeeded in everything he tried. The only thing he has failed to do is make me dance. And I hope he will not try again,” he said in a lighter vein.
The likes of Matthew Hayden and Shivnaraine Chanderpaul have single handedly tormented Indian bowlers in the past. Taking a liking to India’s pace and spin so much that before the bowlers dislodged them, they had reached triple figures; the opposing batsmen left with too much room to cover.But Steve Smith took this fondness for Indian bowling to altogether different proportions with 769 runs in a long Australian summer featuring 4 Tests, finishing off with another ton in the World Cup semi-final to knock India out. If this was West Indies, they would have composed a Calypso by now, “We couldn’t out Smithy at all.” Smith’s home summer against India was as dominant as Gavaskar’s1971 tour of West Indies.”Maybe once you start dominating an attack it’s about sustaining your form all the way through,” Smith says in an exclusive interaction with Headlines Today.”But the hundred in the semi-finals of the World Cup was really great for me. It was a home game at the SCG and a very crucial game,” he recalls. He could well have added it became more fulfilling to silence a predominantly Indian crowd at one’s own backyard.Smith doesn’t just come to the IPL as an in-form player but a World Champion, fresh from winning the game’s biggest prize. “Yeah, it’s been a week since we won the World Cup. It’s been an amazing experience, amazing seven weeks of cricket to play at home and lift the trophy, something I will never forget,” he says reflecting on the World Cup glory.advertisementThree of his Aussie team-mates from the World Cup winning team will be playing for Rajasthan Royals this year; a team he feels a lot more at home than what he did with the now suspended Pune Warriors. Micheal Clarke, was one of the guiding forces at Pune but the team never found the balance or organization strength to compete. Under Shane Watson, this Royals outfit looks richer in strength and strategy.”I haven’t got time to look at the various teams and stuff but what I can say about our team is there are a few who can play different roles for us. It’s a very good squad. We’ve got to take it a game at a time. The start becomes very important,” he says.IPL has always come with its own pressures with ambitious owners wanting victory at all costs but this time around moving from the high pressure World Cup enviornment to franchisee cricket it is bound to be more relaxing for the cricketers. “I will be trying to sustain the form as much as I can. Try and practice a few shots in T20, try and find the next gear. But it’s equally important to keep things simple,” Smith talks of switching to slam bang cricket.Sydney boy Steve Smith is tipped to take over Australian one-day captainship from Michael Clarke but it doesn’t bother him from taking a back seat to captain and vice-captain Watson and Ajinkya Rahane with the Royals.”Look Rahane is a terrific player. He played wonderfully in Australia on our wickets and did well in the World Cup as well. One of the great things about IPL is it allows us to learn different things of each other,” he speaks of his young team-mate who’s stature like him is also quickly on the rise.We asked Rahane, if there is a bit of banter from Smith how India couldn’t stop him getting to hundreds all summer. “No he is our man now,” he replies. Smith concurs. Unlike a lot of his other Australian team-mates, Smith isn’t the leader in the verbal game, just busy accumulating runs.
EAST LANSING, MI – SEPTEMBER 23: Head coach Brian Kelly of the Notre Dame Fighting Irish watches the warm ups prior to the start of the game against the Michigan State Spartans at Spartan Stadium on September 23, 2017 in East Lansing, Michigan. (Photo by Leon Halip/Getty Images)Notre Dame unveiled its “Shamrock Series” uniforms today, much to the delight of the Fighting Irish players. But that wasn’t all head coach Brian Kelly wanted to reveal.Kelly brought walk-on running back Josh Anderson, who was modeling the uniform, out in front of his teammates, but not just so they could get a better glimpse of the jerseys. Kelly wanted to praise Anderson’s dedication to the program, and inform the 5-foot-9, 205-pound senior he was being rewarded with a scholarship. It was all captured on this video, which Notre Dame released minutes ago. Very cool moment. Congrats Josh.
Twitter/@MDFlash_7New Illinois athletic director Josh Whitman wasted no time in making a huge splash. One of his first moves on the job was to fire head football coach Bill Cubit, who took over for Tim Beckman last August. While the sense of urgency is somewhat understandable, given Illinois’ recent troubles, multiple Illini players and signees took to Twitter shortly after the news came out. Apparently that is where many of them learned about the coaching change.Love finding out about this through Twitter. https://t.co/vl1TD6qVVq— Mikey Dudek (@MDFlash_7) March 5, 2016Are you kidding me…— Eli Peters (@the_eli_peters) March 5, 2016… https://t.co/aD2dIQMeHC— James McCourt (@McCourtJ_38) March 5, 2016Wtf….— James McCourt (@McCourtJ_38) March 5, 2016Thank You to @CoachCubit A Great Man and Coach. Forever Thankful for the Opportunities He Gave to Me #Illini— Joseph Spencer (@IlliniJoe71) March 5, 2016WHAT IS GOING ON— Caleb Reams (@SirClutch97) March 5, 2016Backs against the wall, we just gotta fight … Pt.2— Caleb Reams (@SirClutch97) March 5, 2016Learned all this through Twitter, still in shock— Caleb Reams (@SirClutch97) March 5, 2016I’m refreshing my Twitter feed for updates on my own football team for crucial information this is crazy— Chayce Crouch (@teccrouch7) March 5, 2016Haven’t Even Been On Campus A Full Year & Have Had 2 Head Coaches. Now Going On Number 3.— KE’SHAWN VAUGHN (@SpeedKe5) March 5, 2016#IlliniNation Just Stick By Us. We Still Gone Fight.— KE’SHAWN VAUGHN (@SpeedKe5) March 5, 2016It seems that Illinois could have handled this decision better. Hopefully the school does the right thing, and doesn’t stop players and signees from leaving the program now that the program’s second head coach in seven months is gone.