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23 August 2024 at 4:29:04 pm

Fractured Fortress

Jan Suraaj chief Prashant Kishor’s emphatic victory in the Bankipur by-poll, that ended three decades of uninterrupted BJP dominance, is a classic instance when even the safest urban strongholds of a comfortably ensconced ruling party are no longer immune to local discontent and shifting social coalitions. That said, the parallels between Bankipur and the 2023 Kasba Peth bypoll are too striking to dismiss as isolated by-election quirks. In the latter case, the BJP had similarly conceded a...

Fractured Fortress

Jan Suraaj chief Prashant Kishor’s emphatic victory in the Bankipur by-poll, that ended three decades of uninterrupted BJP dominance, is a classic instance when even the safest urban strongholds of a comfortably ensconced ruling party are no longer immune to local discontent and shifting social coalitions. That said, the parallels between Bankipur and the 2023 Kasba Peth bypoll are too striking to dismiss as isolated by-election quirks. In the latter case, the BJP had similarly conceded a seemingly surefire seat that had remained in its grasp since 1995. Both defeats followed the departure of long-serving legislators. Both occurred in constituencies where the BJP began as the overwhelming favourite. By-elections are notoriously unreliable predictors of general elections as their turnout is generally lower, and local grievances loom larger while voters often feel freer to register dissatisfaction without changing governments. Yet they remain valuable political barometers because they reveal the health of party organisations beneath the sheen of national leadership. Bankipur is especially significant because like Kasba Peth in Pune, it represented the party’s urban, upper-caste heartland in Bihar. Prashant Kishor’s victory, therefore, carries symbolism beyond its numerical margin. Making his electoral debut, he converted what had long been considered an impregnable BJP constituency into the Jan Suraaj Party’s most consequential victory. The explanation lies less in ideological realignment than in coalition management. The BJP has, in recent years, sought to broaden its social base by expanding its appeal among the lower caste, economically disadvantaged caste groups. That strategy has served it well nationally, particularly in states where expanding beyond traditional support was essential for electoral growth. Yet every expansion creates new anxieties among an established base. Just as in the Kasba bypoll, the Bankipur result suggests that sections of upper-caste voters, long regarded as among the BJP’s most dependable supporters, felt increasingly alienated. Their perception was that the BJP’s electoral calculations had shifted decisively towards cultivating newer caste constituencies. Kasba Peth offered an earlier version of the same lesson. The BJP entered the contest expecting organisational strength and historical advantage to outweigh local dissatisfaction. Instead, the opposition successfully transformed the by-election into a referendum on complacency, exploiting organisational fatigue and local resentment. Bankipur appears to follow a similar script. Candidate selection became contentious, local anti-incumbency lingered beneath the surface, and the opposition presented itself as the vehicle for voters seeking to send a message rather than engineer a regime change. While this, in no way, implies an imminent collapse of the BJP’s broader electoral dominance, dominant parties ignore by-election warnings at their peril. Safe seats are valuable not because they guarantee victories, but because they reveal the strength of a party’s deepest political relationships.

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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