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By:

Quaid Najmi

4 January 2025 at 3:26:24 pm

Four MLAs miss Thackeray’s meeting

Mumbai: As the rebel six MPs were proudly showcased before the media in a grand event by Shiv Sena President and Deputy Chief Minister, Eknath Shinde, ex-CM and Shiv Sena (UBT) supremo Uddhav Thackeray summoned his entire flock of lawmakers for a headcount – and discovered that four were allegedly ‘missing’, on Monday. The development came after a similar meeting last week of its nine Lok Sabha MPs saw only three in attendance and the six prospective turncoats proclaimed loyalty in the...

Four MLAs miss Thackeray’s meeting

Mumbai: As the rebel six MPs were proudly showcased before the media in a grand event by Shiv Sena President and Deputy Chief Minister, Eknath Shinde, ex-CM and Shiv Sena (UBT) supremo Uddhav Thackeray summoned his entire flock of lawmakers for a headcount – and discovered that four were allegedly ‘missing’, on Monday. The development came after a similar meeting last week of its nine Lok Sabha MPs saw only three in attendance and the six prospective turncoats proclaimed loyalty in the names of their parents and children or Shirdi Saibaba and Goddess Tulja Bhavani – all came to nought as the subsequent dramatic events that unfolded confirmed. Against the backdrop of that ugly butcher-cut, Thackeray had convened a meeting of all SS (UBT) MLAs and MLCs this afternoon. Out of 20 MLAs, 16 were present on Monday, besides five MLCs, as the party fortified itself to keep the hunting wolf away from its pen. A senior party leader assured that the four MLAs who stayed away had given valid reasons for their absence to the top SS (UBT) brass, which is strategising on how to prevent another assault on its strength – the second brazen one in four years. This time, the SS (UBT) leaders are even more nervous as Shiv Sena leader Ramdas Kadam claimed today that “another MP” is veering towards them. Earlier, other Shiv Sena leaders made the SS (UBT) even more jumpy with dark predictions that “at least 14-15 MLAs” would soon join their camp. In Monday’s meeting, Thackeray and other leaders urged the remaining MLAs and MLCs to put up a united show of strength, fan out into their respective constituencies, connect with their party cadres and public outreach, remain aggressive and try to put the government on the mat with burning issues like farmers distress, unemployment, inflation, water scarcity, etc. While reiterating that those who wanted to leave would not be stopped, the Thackeray father-son duo alleged that the Mahayuti was diverting public funds to ‘buy MPs’ while discarding actual governance or implementing public oriented schemes. SS(UBT) lawmakers’ roll-call The MLAs present at meeting: Aaditya Thackeray, Ajay Chaudhari, Bhaskar Jadhav, Babaji Kale, Bala Nar, Dilip Sopal, Gajanan Lavte, Harun Khan, Kailas Patil, Manoj Jamsutkar, Nitin Deshmukh, Pravin Swami, Sunil Raut, Siddharth Kharat, Sunil Prabhu and Varun Sardesai. The MLCs who attended: Anil Parab, Sachin Ahir, Milind Narvekar, Ambadas Danve and Jagannath Abhyankar. The legislators conspicuous by their absence: Rahul Patil (tied up in the Legislative Council counting); Sanjay Derkar and Sunil Shinde (both in their native places); and Sanjay Potnis whose reasons for keeping away were not immediately clear.

AI in Sperm Sorting: An Unbiased Decision for A Better Outcome

Artificial Intelligence or AI is revolutionising fertility treatments of the future. The inclusion of AI enhances the accuracy, efficiency, and objectivity of sperm selection, hence potentially improving fertility outcomes by leaps and bounds. Traditionally, sperm sorting through manual methods is subjective to judgments. Processes like centrifugation and swim-up methods are used to separate sperm based on motility and morphology. Although they are effective, they have their limitations, leading to human errors that affect the success rates of fertility treatment. For instance, studies have shown that traditional sperm sorting techniques can have variability in success rates, with reported live birth rates ranging between 15 per cent to 25 per cent per cycle depending on the method and quality of sperm. Hence the introduction of AI helps in maintaining consistency in evaluations of sperm, using the same data set for every sample which leads to better judgments.


Automation and Standardisation- Automation of sperm selection and also introduction of AI in the process have improved the results in ART. AI-assisted sperm selection improves the accuracy in choosing high-quality sperm for fertilisation purposes, and also, pregnancy and live birth rates might be improved. Technologies like Intracytoplasmic Morphologically Selected Sperm Injection along with AI ensure the chances of pregnancies increase by about 10-20 per cent compared to the standard procedures. AI and Automation will decrease time taken to analyze sperm and increase opportunities to select better sperm with DNA integrity for better development and higher success rates in embryo selection. These processes ensure that the sperm selection process follows consistent criteria, reducing variability in outcomes caused by human error.


Analysing Complex Data for Better Outcomes- AI plays a crucial in improving IVF outcomes by analysing complex data and providing tailored recommendations. AI-driven tools and models such as those on SpOvum.ai point towards an opportunity to optimise ovarian stimulation decisions by assessing patient characteristics and follicle growth patterns. A study revealed that the use of AI in IVF improved egg yield and reduced medication costs. AI enables fertility specialists to make data-driven choices, improving overall IVF success rates and streamlining treatment processes.


Reducing Human Error- AI models can continuously learn and refine their performance by being trained on newer data. This adaptability ensures the technology remains unbiased and up-to-date with the latest scientific insights into sperm quality and fertility success rates. Studies have shown that AI-driven sperm sorting can decrease human-related errors by up to 25 per cent, improving sperm selection quality in terms of morphology and motility.


Reduction of Sperm Damage- The new AI-driven sperm sorting techniques also include microfluidic systems that are known to exhibit several advantages over the most commonly used conventional method, which is centrifugation. Traditional centrifugation methods, such as density gradient centrifugation, also cause severe oxidative stress and DNA fragmentation of the sperm because of the very high mechanical forces involved. The AI-infused microfluidic sorting minimises this damage significantly by involving gentler processes that mimic the natural pathway of sperm selection. The studies show that the process of microfluidic sorting decreases DNA fragmentation in sperm, which gives improved opportunities for success for IVF. For example, DNA fragmentation is 20 percent lower in sperm sorted using microfluidic processes than in traditional processing methods.


AI is bound to play an increasingly definitive role in fertility treatments, which will improve the outcomes for couples experiencing infertility.


(The author is a Co-Founder & CEO at SpOvum® Technologies. Views personal.)

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